In AI in robotics research, Dr. Susanne Bieller, IFR General Secretary noted that programming and integration account for 50-70% of the cost of a robot application. Robot programming was a huge problem for a long time. It was time-consuming and economically unviable for high-mix production as the cost of switching from one product to another was very expensive.
However, the situation is changing dramatically. Thanks to new technologies such as AI and machine vision, robots can be cost-effective even for custom projects or one-of-a-kind products.
Let's take a look at how the two approaches, traditional and new, work and understand the difference.
Let's take for example one part and select several seams. The first is a curved seam with complex geometry. The second is a round seam, which is best done with a positioner (rotating the part while welding). The third seam is a 4-part seam with difficult reach for the robot.
Teach-pendant programming (also it’s called online programming) was developed by robot manufacturers themselves. Using a teach pendant, the operator moves the robot to the desired positions and records the movements. You need to program each point of the robot's trajectories. It should be noted that each robot manufacturer has their own program code and their own approach to programming. If a programmer knows how to work with a robot of brand A, this knowledge may not be applicable to brand B robots.
Traditional teach-pendant programming takes 1 hour 35 minutes to weld these three seams.
Another disadvantage of this method is downtime. Programming takes place inside a cell, meaning the cell will not function during this time. To solve the issue of downtime, offline programming was invented. The idea here is to remove the need to program inside of the cell, moving the process to a virtual environment instead. The programmer still writes the code, but all of this happens inside a virtual twin of the cell.
However, this way of programming created a new challenge that online programming did not present. Virtual and real cells are always slightly different:
Thus, after creating a program in a virtual environment, the programmer still needs to test it on a real robotic cell, using a teach pendant.
So the current method is efficient for mass production where you have to program a part once and then weld it thousands/millions of times.
You just upload a 3D model of the part (from the CAD). The system automatically finds all the weld joints on it. Then you choose the welds and the parameters you need (work and travel angles, offsets, weaving, etc.). No programming is required. Mathematical algorithms automatically generate the robot trajectories. This happens in minutes.
The next step is scanning the part using machine vision. The algorithms compare the previously uploaded 3D model and the real part. The system finds all possible deviations and adapts the robotic trajectories on-the-fly.
In addition, welding often involves fixtures for parts. Robots are also able to "see" them and avoid collisions with them.
The system only takes 10 minutes to set the robot task for welding the three seams described above. It is 10 times faster than the traditional way.
This ease and speed of programming allow simply to switch from one product to another and make robots cost-effective for high-mix production and even one-of-a-kind products.
Here are some examples of the effective use of welding robots for high-mix manufacturing with the new programming method.
Previously, programming a welding robot for one bucket took days or weeks. Now programming takes 10 minutes.
The smart system automatically coordinates the simultaneous movements of the auger and the torch to create a uniform, continuous weld without programming. No need to flip or reposition parts.
Steel Bridge Manufacturer welds more than 50 different part types per month in a single robotic cell. They don't have programmers on staff.
A rehabilitation robot is a service robot for professional use that provides physical and information-related assistance during therapy sessions to rehabilitate sensorimotor deficits after damage to the central nervous system (CNS). The therapy is performed by stimulating physiological limb muscles and peripheral receptors through functional arm/hand and leg movement exercises based on the neuroplasticity principle.
Advancements in robotic technology developed based on neurophysiological and clinical insights have produced encouraging results in the healthcare field. The rehabilitation robots empower patients physically and psychologically in their recovery journey. Studies have found improved enthusiasm in patient participation through the use of engaging gaming and technology-assisted social interaction. The robot also assists rehabilitation practitioners in realising more accessible, efficient, and consistent training while collecting valuable data to assess patients’ recovery progress.
The development of rehabilitation robots dates back to a 1910 patent filed by Theodor Büdingen on a ‘movement cure apparatus’, a machine driven by an electric motor to guide and support stepping movements in patients with heart disease. However, it was not until 1989 that commercial rehabilitation robots took to the market with the development of the MIT-MANUS, which was first tested clinically in 1994 (Robot-aided neurorehabilitation. IEEE Trans Rehabil Eng, v.6 (1) , p.75, 1998, Krebs HI et al.). These devices can assist in activating upper or lower limb movements and motor relearning and developing proprioception, cognitive functions, and attention (Khalili D, Zomlefer M. An intelligent robotic system for rehabilitation of joints and estimation of body segment parameters. IEEE Trans Biomed Eng. 1988;35(2):138–46.). The emphasis has been on achieving high repetitions in interactive and self-initiated therapy to attain a higher functional recovery in a shorter time frame. The philosophy of applying robots in rehabilitation is not to replace the therapist but to widen treatment options (Poli P, Morone G, Rosati G, et al. Robotic technologies and rehabilitation: new tools for stroke patients' therapy. Biomed Res Int. 2013;153872. DOI:10.1155/2013/153872.).
Some of the current commercially available rehabilitation robots are for specific segments of the limbs, not the whole body; they have restricted sensory input and decision-making capabilities. For upper extremity (UE) therapy, it would be reasonable to involve at least the entire upper limb from the shoulder to the fingers because, in practice, people use these parts together in coordination for functional tasks. We can assume that moving the whole upper limb is necessary for restoring efficient inter-joint coordination.
In early mobilisation and treadmill training, gait rehabilitation robots help mobilise the patient into a vertical position, supporting the physiological gait training process and reducing secondary complications. It also provides physical support to caregivers and therapists. Patients can perform overground gait training with wearable exoskeletons as they improve. These robots can serve not only as therapeutic but also as assistive devices.
Many clinical trials and meta-analyses evaluate the efficacy of rehabilitation robots, with mixed results. For UE training, studies indicate improvement in activities of daily living (ADL), arm and hand function, and arm and hand muscle strength (Mehrholz J, Pohl M, Platz T, Kugler J, Elsner B. Electromechanical and robot-assisted arm training for improving activities of daily living, arm function, and arm muscle strength after stroke. Cochrane Database Syst Rev. 2015 Nov 7;2015(11):CD006876. doi: 10.1002/14651858.CD006876.pub4. Update in: Cochrane Database Syst Rev. 2018 Sep 03;9:CD006876. PMID: 26559225; PMCID: PMC6465047.) For lower extremity (LE) training, the Cochrane review published by Mehrholz et al). For lower extremity (LE) training, the Cochrane review published by Mehrholz et al (Mehrholz J, Thomas S, Kugler J, Pohl M, Elsner B. Electromechanical-assisted training for walking after stroke. Cochrane Database Syst Rev. 2020 Oct 22;10(10):CD006185. doi: 10.1002/14651858.CD006185.pub5. PMID: 33091160; PMCID: PMC8189995) suggests that post-stroke patients who received such training in combination with traditional physiotherapy were more likely to achieve independent walking than subjects who only received conventional therapy. Specifically, people in the first three months after stroke and those unable to walk benefited most from this type of intervention. These results suggest that robot-mediated therapy gives certain advantages for patients, at least in motor relearning (Fazekas, G & Tavaszi, I (2019) The future role of robots in neuro-rehabilitation, Expert Review of Neurotherapeutics, 19:6, 471-473, DOI: 10.1080/14737175.2019.1617700.)
The 2010 Stroke Care Guidelines of the American Heart Association (AHA) and the Veterans Administration/Department of Defence (VA/DoD) endorsed rehabilitation robotics for UE post-stroke care. However, the conclusion for LE robot therapy at the time was less encouraging. It states that such robot therapy is much less effective than usual care practices in the US (Bates J et al., Rehabil Res Dev 47(9):1–43, 2010; Miller EL et al., Stroke 41(10):2402–2448, 2010). However, newer studies have shown that a combinatory approach improves motor function in post-stroke arm paresis (Budhota A, Chua KSG, Hussain A, Kager S, Cherpin A, Contu S, Vishwanath D, Kuah CWK, Ng CY, Yam LHL, Loh YJ, Rajeswaran DK, Xiang L, Burdet E, Campolo D. Robotic Assisted Upper Limb Training Post Stroke: A Randomized Control Trial Using Combinatory Approach Toward Reducing Workforce Demands. Front Neurol. 2021 Jun 2;12:622014. doi: 10.3389/fneur.2021.622014. PMID: 34149587; PMCID: PMC8206540).
Treatments using rehabilitation robots enable delegating more manual and repetitive therapy components to robotic devices, allowing a clinician practitioner to take care of more patients in a given time and improving the accessibility of therapy for patients remotely from the comfort of their homes through telerehabilitation. The data collected can objectively assess performance and document compliance and progress using artificial intelligence (AI), promoting data-driven therapy. Virtual reality (VR), combined with haptics, offers therapists more customisable treatment options in a safe environment.
There are still issues to be solved in rehabilitation robots and many questions to be answered, such as efficacy, costs, reimbursement, and regulatory challenges. McKinsey Global Institute mentioned that by 2040, new technologies such as robotics and exoskeletons could reduce the total disease burden by 6 to 10 per cent. Manufacturers, such as Fourier Intelligence, are increasingly investing in research activities by collaborating with established rehabilitation research institutes to innovate and develop new ideas. Such collaborations will allow future rehabilitation robots to:
With the introduction of the RehabHub™ (Figure 1) concept in 56 countries, Fourier Intelligence addressed the affordability, accessibility, and adaptability of rehabilitation robots in clinical settings. Robotic technology is offered as a resource to help reduce the physical burden of therapists and improve efficiency in therapy sessions. Clinical trials suggest that current rehabilitation robots can provide certain advantages for patients. Studies have also identified further potentials to be delivered by rehabilitation robots through future technical development. In the long-term, this will bridge the skills gap, meet the ever-increasing need for rehabilitation services and, ultimately, improve the quality and efficiency of the overall health care system.
Image @ RehabHub™ concept addressed rehabilitation robots’ affordability, accessibility, and adaptability in clinical settings.
Already for the third and obviously not the last time, we wrote the preface of “World Robotics Service Robots” under the influence of the pandemic (not to forget other global challenges, of course). While some things in our private and professional lives have more or less returned to normal, in other areas the effects of the pandemic are still manifold. Some of these effects have an immense influence on the perception and market development of service robots.
The labor shortage is visible in many fields, e.g., in restaurants, at airports, or in the crafts. Service robots have the potential to provide support and relief here and we already see some solutions like smart transport robots bringing dishes to the guests or a startup offering a painting robot. Of course, big players also invest in robotics. With about 300 suppliers in the field of logistics (out of approx. 1,100 in total worldwide), this is still the strongest market. Assistance at home has also become an even more important topic and strengthened the sold units of vacuum cleaners and lawn mowers.
In general, the situation we all had to deal with strongly supported the acceptance of technology and digitalization. This sometimes created a hype for new robotic solutions and now we start seeing some consolidation of this development. An example is the development and growing market for disinfection robots. Some sort of renaissance can be observed for four-legged robotic devices, which, however, are often still used remotely. Bipedal robots are under development again. A new development can be seen in agriculture. The question of sustainability and the ban on glyphosate raise the need for new technological solutions like agriculture robots that can, for example, mechanically remove weeds. Long story short: The service robotics market is growing and opening up completely new opportunities for many companies. This dynamic is reflected by more than USD 17bn of venture capital that was invested in (not only service) robotics in 2021, almost three times as much as in the year before.
As was the case in prior years, large growth markets are contrasted by small, highly specialized niche markets, with many startups joining the fray and other companies unable to establish themselves on the market.
In close cooperation, Fraunhofer IPA and IFR are observing more than 1,000 companies worldwide offering service robotics solutions (amongst them are about 12% startups). Both, the professional and the consumer service robotics domain benefit from recent technical innovations: Fundamental developments in the fields of digitization, cloud technologies, 5G and artificial intelligence, specifically in machine learning, are leading to a technology push in service robotics. The free Robot Operating System ROS continues to be extremely popular and enables a quick start to the development of service robot applications even with few own resources. New virtual market places enable ease of deployment and use, more standardization, and thus not less than the “democratization of robotics”, as could be observed on the important trade fairs like Hannover Messe, Automate in Detroit or automatica in Munich.
On the other side, we see a strong market pull, specifically for professional service robots. New business models at the same time significantly lower the financial barriers to decide for the use of a service robot in volatile markets. A prominent example is “Robot-as-a-service” which means that the user only pays for the tasks the service robot fulfilled successfully.
Author see below, Co-Author: Dr. Kai Pfeiffer, Head of the Group “Industrial and Commercial Service Robots” at Fraunhofer IPA
Picture: KEN Hygiene has developed a fully automated sterile center using autonomous mobile robot that works as the logistical link © MIR
The growing number of robots in mass production is part of a decades-long success story in relieving people from the burden of repetitive, ergonomically difficult, physically demanding and even dangerous work. Highly efficient six-axis robots and Scara or Delta systems ensure consistent quality in welding, painting, machine loading and workpiece processing tasks, quickly and around the clock. New, collaborative robots working side by side with people, plus numerous technological advances in programming, diagnostics and accuracy, have paved the way to a wealth of highly economical solutions in a wide range of uses. For proof of this success, look no further than to the over 400,000 robots installed every year.
When it comes to robot-assisted painting, the principle of use is basically the same: A tool, the paint atomizer, is moved along an object and continuously applies paint while operating with consistent, repeatable quality. Everything needed for painting, such as paints and solvents and the application technology with pumps, color changers and mixers, is carried along with the tool.
Taking a closer look at the requirements specific to painting soon reveals that these tasks cannot be solved using standard robots, which is why every manufacturer uses a number of painting robots tailored to the respective painting processes. In other words, the painting robots are modified to suit the application and not vice versa. Special characteristics include:
Combining the implementation of these characteristics in the painting robot with the application technology and intelligent control and operating software produces optimal painting results while maximizing production efficiency. Application technology manufacturer Dürr Systems AG has incorporated these characteristics in a comprehensive range of painting robots. Given the right painting booth configuration, all vehicle models can be painted inside and outside fully automatically.
Efficient production should ensure sustainable, flawless painting processes with minimal media consumption, the best possible application efficiency and the lowest production downtime. We still have a way to go yet, but high-rotation atomizer technology will ultimately optimize application efficiency in this area.
Innovators in the application technology industry are developing solutions to reach the goal of overspray-free application. A special feature of this technology is the ability to apply paint with high edge definition. In this process, the painting robot moves an applicator along the object to be painted, while maintaining an accuracy in the range of a few tenths of a millimeter. Thin needle valves in the applicator can be individually opened and closed as needed to produce an application pattern of any design. The robot and its integrated measuring equipment ensure the requisite accuracy while smart software tools simplify programming. Initial applications include decorative paint finishing, such as two-tone body roof painting and painting motifs of all kinds on the engine hood. Promising solutions have been put to practical use in the first customer applications.
Although painting robots will remain niche products in terms of sheer numbers, the innovations they embody will continue to make substantial contributions to sustainable and efficient production processes. We look forward to what the future holds in this sector.
Image: Fully automatic interior painting of automotive bodies © Duerr Systems
As we consider the present global environment at the mid-point of 2022, it’s increasingly evident that we continue to witness an unprecedented series of irrepressible events. Although now normalized in most global regions, the effects of the coronavirus pandemic continue to persist in compromising global supply chains, subsequently prolonging the scarcity of critical components and further exacerbating the effects of the global labour shortage. In addition, the war in Ukraine has caused heightened levels of global geo-political tension, resulting in soaring inflation and an imminent energy crisis of potentially immense proportion.
With the effects of these global instabilities set to continue for the mid-term period, it is not only imperative we continue to work collectively as a global community to avoid an economic downturn, but essential that industries and business look towards more sustainable and agile operational strategies to ensure a wide range of risks are mitigated and the surge of demand witnessed in 2021 can be successfully fulfilled.
The industry statistics - as presented in World Robotics 2022 Industrial Robotics - provide the strongest indication to date that robotics as a technology is making a fundamental contribution towards supporting industries and business to immunise their core production processes against the outcomes of each global crisis we experience. Despite all global headwinds and the continued presence of the pandemic, a record 517,385 new robots were installed across all industries in 2021, a significant 31% higher than in 2020, with the electrical / electronics, automotive and metal industries continuing to be leading adopters of the technology. Global robot stocks reached almost 3.5 million units, 15% higher than in 2020, the associated value of installations reached an estimated $15.7 billion with the global average manufacturing density 126 robots per 10,000 employees.
These are highly impressive results and a reflection of several contributing factors. Naturally we have witnessed a rebound effect from the global contraction of 2019 and 2020, but also influential is the impact of the ever-increasing research and development efforts of all robot manufacturers who are leveraging digitalization and AI to advance robotic functional capability to be more widely deployable into non-industrial applications such as warehousing, logistics and medical. Recent advances in both traditional and collaborative industrial robotics demonstrate that major advances in user requirements have now been achieved, including much improved ease of use, intuitive and smart programming capabilities and improved software compatibility. These new features are attracting many new users to robotics from small enterprise to global OEMs. Industries characterized by high mix, low volume production can now take advantage of robots to achieve the desired levels of agility and flexibility in manufacturing. Complex tasks can now be managed in coexistence with human workers to achieve elevated levels of productivity.
As we look forwards to 2022 and 2023, we recognize that being able to respond to and successful navigate the many challenges that will influence businesses and industries will be imperative to sustain economic growth. We believe strongly that robotics will play a fundamental role in securing a manufacturer’s ability to meet the changing demands of industry and technology and promote a strong competitive advantage to those who begin the journey to automate with robots.
Picture © YASKAWA - robots assemble robots for automation of the factory
ROS, the Robot Operating System, is an open source software framework, more recently referred to as a development kit for robotics application development. For over 10 years ROS has become a standard platform to enable developing teams across technical domains and industries to transition capabilities from the research lab to the field or factory floor by providing access to proven algorithms, developer tools, and interfaces for the various components that are needed for the next generation robotics deployments. It has enabled disparate components to work in a tightly integrated way to solve complex tasks or realize capability where dynamism is a key element of the environment or application.
The success of ROS is a testament to the success of open source as a vehicle for advancing capability and the community that has built up the vast code base while demonstrating over a decade of capability. This success is helping to convert new adopters as ROS transitions to ROS 2 while introducing more robust features. As the robotics community transitions from the original implementation of ROS to ROS 2 and further deployments enter the wild, it helps to look back at the history of ROS and the related ROS-Industrial initiative to help contextualize the current trends and think about the exciting future ahead.
ROS got its start in California’s Silicon Valley at Stanford University in the U.S., as the foundational framework within the 2008 Willow Garage PR2 robot. From there, after Willow Garage was shut down, a nonprofit was started to support ROS and the complimentary simulation framework Gazebo. Since then, Open Robotics has led the maturation of ROS, enabling and growing a global community that is multi-domain, supporting the teaching of robotics, single student projects, multi-institution collaboration, competitions, and of course new products in the marketplace. The value has been proven over and over again by leveraging an open source, business friendly license model, that accelerates time to market. This has enabled more efficient returns by enabling derisking and more agile end-use application development. ROS provides consistent flexibility to enable efficient integration with other ecosystems, software tools, or hardware by providing well documented interfaces, and messaging architectures.
After the success of ROS, the downloads, the products, and the sizeable community, it was time to look at the shortcomings. This led to the development of ROS 2. The initial release of ROS 2, in December 2018, sought to address several limitations in ROS 1. The robustness and determinism in dynamic environments, security, and support for embedded systems were key drivers for the redesign that went into ROS 2. The other key element was the selection of the Data Distribution Service (DDS) communication standard, which has been proven in critical infrastructure, military, and financial system applications. This has addressed a number of the challenges around reliability and enabling more robust performance and best in class security.
In parallel to the progress of ROS, an initiative was launched in 2012 to understand if ROS could be leveraged for industrial applications. Southwest Research Institute, a nonprofit, applied R&D organization based in San Antonio, Texas, had been building first-of-a-kind robotic systems for the previous 20 years. Each custom application would require significant software rewrite due to the nature of industrial robotics creating proprietary ecosystems, including their own proprietary programming languages. Shaun Edwards of SwRI, in cooperation with Yaskawa Motoman, co-located at Willow Garage to create the first instance of an industrial manipulator being controlled by ROS. This commit and creation of a simple message and the Motoman Driver were the first ROS-Industrial commits, and the ROS-Industrial open source project was born. In 2013, Paul Hvass, also of SwRI, instantiated the ROS-Industrial Consortium. The Consortium’s mission is to give direction to the ROS-Industrial open source project and drive synergies amongst universities, OEMs, solution developers and providers, and end-users. The ROS-Industrial Consortium Americas has been managed by Matt Robinson of SwRI since 2017, overseeing enhancements to open source resources and the growth by more than double of the Consortium membership.
Since the inception ROS-Industrial has sought to bring high mix/low lot capability to industrial end-users, while reducing barriers to entry both in industrial robotics as well as open source robotics. Over the course of its history ROS-Industrial specifically has provided resources that include applications, training, standards for interfaces, as well as physical systems and demonstrations aligned with industry needs.
As part of the vision for ROS for industry, which is fed by feedback from the Consortia members and the industrial community, is to manage the transition and support for ROS and ROS 2. There have been numerous documented industrial successes with ROS, and collaboration projects furthering foundational capability for industry. However, as ROS 2 becomes the new standard, a new approach for support has been required. Therefore ROS-Industrial has sought to create key enabling content decoupled from the ROS version as feasible, and provide interfaces for the specific ROS version that is being used. This enables those that are not ready or have high performing systems in ROS 1 to continue to leverage improvements in core libraries. Conversely as new users adopt ROS 2, they can count on core libraries that have been proven in industrial applications. The main thing is to create as big of a tent as possible, and not leave users behind simply because they cannot migrate to ROS 2, while still enabling continuous improvements in the ecosystem as more adopters come on, creating higher performing and robust solutions for the whole community.
The impact of ROS-enabled solutions has been well documented. Spirit AeroSystems has shared their success in leveraging ROS for high-mix part painting. Due to their position as a supplier to numerous OEMs for aerospace, they inherently have the challenge of producing parts of many varieties. In this example ROS enables them to do on the fly Scan-N-Plan painting, improving their efficiency and removing the burden of creating unique robot programs for all the parts for which their operations were responsible. Since then, Spirit AeroSystems has grown a strong team of internal developers where ROS is a key enabler in their Industry 4.0 vision and how they manage total value stream productivity and quality.
Another case study is looking across two recent development initiatives. The first is the Advanced Automation for Agile Aerospace Applications (A5) program. The United States Air Force funded this initiative to create a flexible agile platform and software that could easily go from one air depot sustainment task to another without complex programming. Currently the program is in a follow-on phase to execute radiographic inspection for obstructions in air inlets, after performing sanding repair operations in a previous phase.
While this application is compelling, the real impact has been the associated software framework. This framework built on ROS has recently been extended to two new applications as part of the ARM Institute, which serves as a Manufacturing Innovation Institute in a public-private partnership funded by the U.S. Department of Defense. The first program, Mobile Autonomous Coating Application for Aircraft Sustainment sought to create a mobile robotic paint solution for high-mix aerospace parts. The second, Autonomous Coating with Realtime Control and Inspection, sought to do real time paint process planning based on observed features and adjusting the paint process from a learning framework informed by extensive computational fluid dynamics. What made these programs possible, each only a year in length, is that they were simply extensions of the A5 framework. The modular nature with consistent interfaces enabled new components, or software modules, to be added and the core framework re-used to create these two new applications for two different end users.
Since 2013, the ROS-Industrial open source project and affiliated Consortia have grown to be a global initiative. Fraunhofer IPA in Stuttgart, Germany stewards a ROS-Industrial Consortium European Union (EU) since 2014 and the Advanced Remanufacturing Technology Centre in Singapore is headquarters for ROS-Industrial Consortium Asia-Pacific (AP).
Within the European Union the recently completed ROSin project was funded by the EU’s Horizon 2020 research and innovation program and aimed to amplify its impact by making ROS-Industrial better and even more business-friendly and accessible. The success of this program has furthered robust interfaces supported by OEMs, the creation of new applications around welding and logistics, and numerous new startups leveraging ROS in their products within the EU and beyond.
ROS-Industrial Asia-Pacific has been creating its own momentum and contributing to the global ecosystem. The biggest program has been supported by Open Robotics, the curators and maintainers of ROS and the Singapore government. The Open Robotics Middleware Framework (Open-RMF) is a free, open source, modular software system that enables sharing and interoperability between multiple fleets of robots and physical infrastructure, like doors, elevators and building management systems. The work was recently recognized as one of the 2021 RBR50 Robotics Innovation Award Honorees. Interoperability has been a mainstay of one of the benefits of ROS and this work highlights the power of enabling rich interoperability across multiple intelligent devices.
It is clear that ROS has now gained a foothold in the robotics ecosystem. The ability to stretch from education to research labs to novel product developers, to the top tech companies and end-users on shop floors leveraging ROS to create solutions is truly compelling. Numerous companies have built and delivered products that leverage ROS or are using ROS as part of the development workflow and they include the likes of Clearpath, Fetch, now part of Zebra Technologies, Samsung, Apex.ai, Sony, Robotnik, Bastian Solutions, and more. There are ever more resources to support industry to adopt ROS. These include workshops, education and training, working examples, and regular community and developer meetings and forums to engage with others using these tools, and even conferences, both around ROS and for each global region for ROS-Industrial.
As ROS 2 progresses in parallel with industry adoption, there has been increased focus on safety and quality. New resources are emerging and practices to ensure enhanced security and performance for systems that leverage ROS. There are numerous working groups that are open and active seeking to build a broad coalition to improve the framework to support requirements and enable an ecosystem that is scalable for industry, education, government, and beyond. Recent initiatives around ROS for space only add to the requirements that will push ROS relative to capability and reliability due to the requirements for software in that domain.
We look forward to seeing the continued growth of ROS in industrial use and deployment and believe strongly in a community that focuses on the foundational building blocks that provide a foundation that reduce the reinvent the wheel, enabling end users with challenges to get right to the problem solving and having tools, resources and software ecosystem that just works. We encourage those interested in advancing the state of industrial robotics to consider looking into ROS and the ROS community, including projects like ROS-Industrial, and the specific community around ROS for industry. Let’s continue to provide resources to enabling richer industrial capability aligned with the needs and requirements of the factories of tomorrow.
Are humans still at the center of innovation? This question is at the heart of the debate on roboethics, a topic that SIRI identifies as fundamental to the future development of robotics. "Human creates and has always created his tools to improve work - explains SIRI’s presidente Domenico Appendino, tracing the history of robotics - but also to reduce risks, fatigue and protect his health. For this reason, tools are deeply linked to the social and ethical aspects of man throughout his history. If we look at the history of robotics, we can see that the theme of roboethics has also been addressed in literature, starting from Asimov's famous Laws of Robotics to the play 'RUR, Rossum's Universal Robots'. Today, in this manufacturing scenario, these themes are still important and it is therefore essential to analyze them".
Paolo Benanti, professor of Moral Theology and Ethics of Technologies at the Pontifical University, stresses that the future challenge will not be between human and robot, but between human with robots and human without robots. In this future that perhaps it’s already our present, Benanti points out another essential dichotomy: the one between algoethics and algocracy. "Algoethics - explains Benanti - was born in response to what is called algocracy, i.e. the 'dominion of algorithms', a society based on the massive application of algorithms. It becomes necessary to study the ethical problems and social implications (but also political, economic and organizational) arising from the increasing use of information technologies".
For Andrea Bertolini, researcher and director of the EURA Center of Excellence on the regulation of robotics and AI, maximum attention must be paid to the definition of the regulations that will govern the development and applications of artificial intelligence systems. "There is a European regulatory interest - highlights Bertolini - and it is the so-called 'Brussels effect', i.e. the first to formulate rules defines them for all players (including other countries). This is a very important game and should be considered an opportunity for innovation. This regulatory activity will be fundamental for the development of European robotics".
Talking about robotics, it is important to take into account also the concept of social robots, i.e. those robots whose purpose is to welcome and assist people. "The goal - explains Antonio Sgorbissa, professor at Dibris University of Genoa - is to create robots that have also cultural competences, meaning that they are able to adapt their acting according to the person in front of them. Social robotics enlights issues worthy to be considered in other contexts, i.e. determining the trust of the operator towards the machine, making the algorithms capable of explaining their choices and their working methods and, finally, developing autonomous machines capable of recognizing different cultures and acting accordingly".
“It is important to stress out” - Appendino concludes - "that industrial robotics is still very far from many of these experiences that, instead, concern bots, i.e. artificial intelligences working on computers. However, the progress is so fast that these themes could be here tomorrow, without almost realizing it. In the meantime, we see the very idea of company and society changing, with the worker becoming a machine operator, more and more similar to an employee. I conclude, however, by recalling that a knife can serve a mother to prepare a meal to her child, and a murderer to kill someone. The difference is always how a tool is used: the same happens with robots that, let's remember, are not friends or workmates, but tools used by those who manage them and, still for a long time, not able to self-determine".
For many robotics manufacturers, enabling such an approach will require far-reaching adjustments across the entire product cycle. While after-sales service is already an established part of the business model for most, ensuring reparability on a large scale and over long periods of time will require new approaches to storage for spare parts, extended service infrastructures and, ultimately, recalibrated business models. So, is the right-to-repair movement a pain for the industry? Not necessarily. With the right strategy in place and some willingness to adapt, the shift towards a more service-oriented industry can benefit customers and manufacturers alike.
How can manufacturers make sure they don’t get overwhelmed by an incoming flood of new repair requests? One way is to bring down the service interventions needed in the first place. A focus on reliable products that will run without major problems for a long time is a first and crucial step towards providing excellent service. For automation companies this means to test and refine the reliability of their products under real-life conditions. All production sites of FANUC, for example, are almost fully automated using its own robots and other products, which gives us a clear understanding of their capabilities. In addition, we maintain a 20,000m2 Reliability Evaluation Building where we subject our robots and other products to a range of stress tests, to analyse in detail their long-term resistance to harsh production environments.
There is another aspect that needs to be considered as early as the product development process: Manufacturers should create products that allow easy access and reparability further down the road. While this might entail some initial investment in a smart design, such a product will save significant service and repair expenses as the robot enters the maintenance cycle. Our answer to this challenge for decades has been “Use less parts” when designing new products, as less parts translate into lower risk of future failure.
Still, for manufacturers it is easy to lose their know-how of products that they brought to market a long time ago. Therefore, to offer long-term repair to customers, repair capabilities need to be build up early on. At FANUC we stock up on electrical components and spare parts as soon as we decide to discontinue our products such as robots. By thoroughly analysing production numbers and taking into account an average service life of sometimes more than thirty years for our robots, we accumulate those parts in our warehouses and repair centers around the world. Even after that, FANUC can recondition all spare parts in our own Repair Centres and make them available to customers as long as they use our robots.
In Europe for example we have reached a local spare parts availability of 99.97 percent for the year 2021. This means that only once in every 4.000 cases we did not have a necessary spare part on stock in Europe and the part needed to be shipped from another FANUC location around the world. This included spare parts for products that have long been discontinued. Thanks to this high spare parts availability and a dense network of service locations throughout Europe we managed to achieve an average repair time of less than 20 hours for our robots – from the initial customer call to putting the robot back in operations. Impressive as this might be, when it comes to service, time is of the essence – as every hour of downtime the customer will lose money.
While the benefit for the customer is easy to see – the question arises how operating such an elaborate and extensive service operation does not become a massive drain on a manufacturer’s resources. A realistic answer needs to acknowledge that shifting the business model towards such a “Service First” approach is no small change process and will likely require substantiate investment supported by a strategy for long term customer satisfaction. While few companies already offer something similar to a “right to repair” for their customers, manufacturers that might want to start moving into a similar direction will need to get over some speedbumps along the way. In the long term, however, a robust and attractive offering around after-sales services will allow them to earn customer loyalty and even open up new revenue streams, all the more so as digital technologies like predictive and Assisted Reality supported maintenance are making it easier for customers and manufacturers to respond with speed as well as diligence. Thus, the effort is not only likely to pay off – in times where customers’ expectations around service are changing, manufacturers that don’t get on board risk getting left behind. The sooner they start their transformation towards longevity of products and reliable repair and maintenance services, the better prepared they will be for the challenges ahead.
image: © FANUC
There is considerable misunderstanding around the role of AI in robotics. Human-like robots with super intelligence are standard fare in entertainment, while terms such as ‘robotic process automation’ and ‘bots’ refer to software applications with no physical robot.
To separate fact from fiction, the IFR has just published ‘Artificial Intelligence in Robotics’ , in consultation with members and experts. The paper looks at current applications of AI in robotic applications, future directions, and safety and certification considerations.
Artificial intelligence opens up new possibilities for robotic automation. The growth of customised production, with frequently changing products, orders and stock, and the rapid rise of e-commerce, have made variability and unpredictability a common feature of manufacturing and logistics sectors. Uncertainty is also inherent in public environments where healthcare or assistance robots, for example, are at work.
In these situations, AI enables robots to sense and respond autonomously to their external environment in real-time, for example identifying objects to be picked from an unsorted bin, or automatically identifying welding points on a new part.
AI also holds potential for reducing the time and resources needed to programme and re-task robots. Programming and integration account for 50-70% of the cost of a robot application. This, together with the time and cost of re-tasking a robot to the requirements of a new production run, have made automation economically unviable for many small-to-medium-sized companies (SMEs), or for larger manufacturers and wholesalers with high product variance. Experts estimate AI could ultimately halve the time required to programme a robot, as well as significantly cut the time needed to re-task it.
It’s important to note, however, that AI is not necessarily a prerequisite to enable robots to respond in real time to their environment. Many ‘pick-and-place’ applications, in which the robot identifies an object to be picked and determines how to approach and grasp the object, do not require AI. However, the greater the level of variability and uncertainty, the more likely it is that AI algorithms will bring cost-benefits over traditional, deterministic programming. For example, while mobility does not require AI, capabilities such as determining whether a person encountered by a mobile assistance robot is an adult, older person, or child, and then responding accordingly, would either be impossible, or require unrealistic amounts of computing power to achieve, without AI.
The fact that AI algorithms enable robots to act autonomously raises questions around safety. However, robot applications comprise many different levels of software. Currently, the safety layer is hard-coded – for example, ‘stop if an object is less than 10cm away’ – and does not use AI. This may change in the future – for example AI may be used to determine how fast a robot should slow down, based on the trajectory of the object or person in front of it.
European authorities are currently reviewing regulation on AI in robotics. The global robotics industry is concerned about the current drafts of the European Machinery Product Regulation and the AI Act, particularly with regard to the proposed requirement for mandatory third-party certification of AI-enabled robots (vs. manufacturers’ self-declaration of conformity with safety standards as is currently the case). This would impact any company selling robots on the European market. In the long run, the new regulation will disadvantage European companies, especially SMEs and start-ups. The IFR is also worried that the relevance of international standardization - a cornerstone for the safety of robots around the globe - might shrink if the European Commission mandates the development and adoption of EU-specific technical specifications. The IFR therefore calls on European policymakers to amend both drafts to balance the protection of citizens with the market’s need to adopt new technologies and ensure a level-playing field for companies.
After years of development, China has become an important player in the global robotics industry. On December 28, 2021, China's Ministry of Industry and Information Technology, the National Development and Reform Commission, the Ministry of Science and Technology together with other 12 departments jointly issued "The five-year development plan for the robotics industry in the 14th Five-year" (hereinafter referred to as " The Plan"). This is the second five-year development plan for the robotics industry in China (The first five year plan for the robotics industry (2016-2020) was released in June, 2016), and it plays an important role in guiding and promoting the high-quality development of China's robotics industry during the 14th Five -Year period.
Robotics research started in the early 1970s in China. However, since China was in early stages of industrialization, with an immature market, robot adoption was slow. With the rapid development of China's economy, in the 21st century, especially since 2010, China's robot industry has entered into a period of rapid development driven by market demand and government policies. In 2013 China became the world's largest industrial robot market. Recent years have seen a new era of technological revolution and industrial transformation and the deep integration of robotics with next-generation information technology, biotechnology, new energy and new materials, leading to unprecedented development opportunities for the robotics industry. The Plan stipulates that during the "14th Five-Year" period, the industry should focus on high-end and intelligent development, centering on five main tasks that give clear direction for the development of China’s robot industry:
Robots already play an important role in industry and society – for example as a platform for emerging technology and as a cornerstone of modern industry, driving the digital development and intelligent upgrading of industry, but also as a vital tool to deal with population aging and generally improve people's quality of life. People have increasingly high expectations of robots that are more intelligent, easier to use and safer. In response, the Plan proposes a focus on the innovation and application of the following types of robots: welding, vacuum (cleaning), explosives production, logistics, agriculture, mining, construction, healthcare, elderly care and disability assistance, security, epidemic prevention, household robots, public service robots, underwater robots, collaborative robots, mobile robots, and robots able to work in dangerous environments.
China has been the world's largest market for industrial robots for eight consecutive years, and robot density in manufacturing industries reached 246 robots per 10,000 employees in 2020. Industrial robots are used in 52 ‘major’ industry sectors such as automobile, electronics, metallurgy, lighting industry, petrochemical and healthcare, and 143 ‘medium’ sectors (according to the UN’s classification, China's manufacturing industry covers 41 major categories and 207 medium categories.) Service robots are already deployed in wide sectors such as warehousing and logistics, education and entertainment, cleaning services and healthcare. However, deployment is still not keeping up with economic and social development and people's expectation of a better life. Expanding the depth and breadth of robot applications in China in the next five years is therefore a priority for the robotics industry in China. The Plan specifies an application-focused approach to guide and accelerate the updating and upgrading of robot technologies, and promote the high-quality development of the robotics industry in China.
Executing The Plan will not only support the sustainable and healthy development of robot industry in China, it will also drive progress in robotic technology and industrial automation globally.
Direct link to the full text (in Chinese language).
Image © RISONG
As the 20th century began, many people thought robots would be part of everyday life by the year 2000. Although that vision hasn’t materialized, modern technology makes it a lot more feasible. Today, robots are most widely used in the industrial sector. In fact, the global population of industrial robots is around 2.7 million, most of which perform 3D (“Dirty, Dull, and Dangerous”) industrial applications that are repetitive and monotonous. These robots use first-level software and protocols to communicate with other machines, telling them when to start rotating, when to start moving, and understanding when the work is done. However, interoperability and communication remain a challenge when multiple makes of robots and programmable logic controllers (PLCs) are engaged on common tasks. Without communication via a common platform, the flexibility to interchange these machines based on changing production requirements is poor. Fortunately, there is a solution.
Just as collaborative work and collective intelligence played a very important role in human progress, collaboration is key to enabling robots’ effectiveness. Various open-communication protocols are being developed to ease robots’ connection with software systems and improve their collaboration. Such ongoing software developments are critical to the continued evolution of robots.
As the need for robotics capability increases, robotics software will need to evolve. The next evolution for robotic collaboration requires robots to make simple decisions. These decisions will be uncomplicated and objective – deciding whether to pick the red one or pass the blue one – but even basic decision-making is necessary to meet flexible production-line requirements. Industrial robots can operate now with a low level of intelligence to meet the demands of a well-planned batch production line. But that will soon change when production lines transform to high-mix low-volume scenarios required to suit growing consumer demands for customization.
Development of robotic software must be composed of flexible, modular blocks (such as interchangeable high-level architecture) and standardized hardware so it can be easily tailored with minimal changes. This will be necessary to address an assortment of application domains like automotive assembly lines, white-goods testing lines, heavy engineering welding lines, etc. The modular architecture will help developers keep pace with changing requirements.
As with any type of software, robotics software comes with unique challenges in networking and security. For robots to evolve, they will need to stay online in closed networks. But as more robots join a network, securing the network becomes more critical. Unfortunately, attempts to hack robots will increase in the future and multiple custom security layers need to be developed for better protection. The next step for robotics will be helping machine communication evolve from early languages (Sumerian languages) to modern languages such as Python, Ruby, Scala, etc., at scale. Adopting the modern languages will provide enormous benefits in terms of integrations with applications that are already in use – for security, communication, and to help robots adopt sight, touch, feel, and thinking at a much faster pace. And, with AI algorithms living in the cloud, robots can synchronize seamlessly, and learn collectively from the experience of a single robot, because robots can act from a common “brain.”
Globally, some countries have already embraced a robot-friendly environment. In Japan, personal robots are trusted with taking care of the growing elderly population, and in Korea, thousands of robots are deployed as teaching assistants in kindergartens. Yet Americans have been much less eager to accept robots as part of their daily life, with most robotic growth happening in the industrial sector. Robotics is still a young and multi layered industry. And today’s robots are just the tip of the iceberg.
To promote more enthusiasm, acceptance, and enable robots to meet their potential, technologists should focus on software. Consider early mobile phones, which remained “dumb” and only connected people by voice until they could be integrated with software applications. Today, mobile-phone hardware has become largely commoditized; it is the software that defines a device’s capabilities. The amazing possibilities that are continuously opened by smart logic and complex algorithms have contributed to today’s wide spread opinion that apps can do everything.
Robotics will follow a similar path. As hardware becomes commoditized and the possibilities of apps on robots become endless, we will once again hear, “there is an app for that.” The future of robotics will be as varied as the current mobile-computing environment. There will be applications extending to robotic shopping based on personal preferences, customized teaching tailored to unique psychological profiles, health monitoring and management personalized for each patient, and leisure travel guides personalized for every traveler (around and outside the earth). The possibilities are endless.
The concept of software-controlled robotics and automation is in a budding stage. However, the robotics software market is poised to grow at a rate of 45.5% CAGR from 2021 to 2026. Wipro Robotics, as an early entrant in this field, has developed and deployed software-controlled robotic applications in a range of industries. From this experience, it is clear to us that software evolution in robotics is critical to human acceptance of robotic technology. Companies deploying robots today should cultivate the inclination to maximize their flexibility and intelligence through robotics software to step into next level of productivity. This will help set the stage for the next generation of robotics.
© teaser picture iStockphoto
The challenges caused by the coronavirus pandemic continued in 2021 – for many of us much longer and tougher than we had expected back in the summer of last year. However, after many “lessons learned”, with a variety of new concepts and many compromises in private and professional everyday life we approach the “New Normal”. This summer, first meetings and business travels were possible again, more and more people are vaccinated, and we hear some good news about the worldwide economic recovery.
“Good news” is an appropriate buzzword for the service robotics market. As it is the case with every edition of the “World Robotics Service Robots”, it presents numbers and market data from the previous year. As was the case in prior years, we are seeing significant growth figures in some sectors. The service robotics market is a broad field that is sometimes developing in very different ways. Large growth markets are contrasted by small, highly specialized niche markets, with many startups joining the fray and other companies unable to establish themselves on the market.
In close cooperation, Fraunhofer IPA and IFR are now observing more than 1000 companies worldwide offering service robotics solutions (amongst them are about 17% startups).
One of the most prominent applications for fighting the coronavirus is cleaning and disinfection robots (professional cleaning). Increased hygienic demands have helped opening this new niche for service robots. More than 50 companies are now offering disinfection robots. We even see some product evolution already, with recent UV disinfection robots being smarter than the old ones, e.g. being equipped with infrared cameras to detect humans in the environment and avoid harming them with the UV light.
Companies delivering food or purchases are facing a rapidly growing demand. Due to this growing interest, a worldwide spread of food and medication delivery robots could be observed this year. That is also why the market for robots supporting last mile deliveries should face a remarkable growth. This growth strengthens an already successful market, since AGVs and mobile robots have been among the fastest growing segments in service robotics during the last years.
Besides the mentioned areas experiencing a strong push through the pandemic, several other domains within service robots for professional use are on the rise. Considering the number of units sold, inspection and maintenance, as well as hospitality robots show significantly rising numbers. With respect to the systems’ value, logistics, medical, and agricultural robots are leading the market.
Consumer robots have also experienced strong global growth thanks to three mass-market product categories: domestic floor-cleaning robots, robo-mowers and robots for education and social interaction. In addition, as in the previous years, the variety of assistive robots available to support handicapped or elderly people (care at home) continues to increase.
Both, the professional service robotics and the consumer robotics domain benefit from recent technical innovations: Fundamental developments in the fields of digitization, cloud technologies, 5G and artificial intelligence, specifically in machine learning, are leading to a technology push in service robotics. On the other side, we see a strong market pull, specifically for professional service robots. Besides the coronavirus, this is caused by current challenges, such as the lack of skilled workers in several professions, demographic changes, or sustainability requirements. Using service robots can help companies to improve their competitiveness and innovative strength. New business models at the same time significantly lower the financial barriers to decide for the use of a service robot in volatile markets. A prominent example is “Robot-as-a-service” which means that the user only pays for the tasks the service robot fulfilled successfully.
The “World Robotics Service Robots” has established itself as the widely acknowledged reference publication in statistics, forecasts, market analysis, and profitability of robot investments. Robot suppliers, media, government bodies, financial analysts and technology scouts are among its readers. It specifically provides an overview of the numerous service robot manufacturers worldwide.
In case you have any suggestions or further inquiries related to service robotics, please do not hesitate to contact us!
Author see below, Co-Author: Dr. Kai Pfeiffer, Head of the Group “Industrial and Commercial Service Robots” at Fraunhofer IPA
Picture: KEN Hygiene has developed a fully automated sterile center using autonomous mobile robot that works as the logistical link © MIR
We are living through an era of historic transformation. While the way we live and work has changed more in the past year than in the previous 30, the underlying trends driving that transformation haven’t changed – they’ve simply accelerated with the pandemic. Industries and organizations are realizing the role of automation in boosting productivity, enhancing business continuity, and enabling the flexibility required to maintain and grow revenue during the pandemic.
In 2021, we are seeing the potential for recovery and investment after the crisis, despite headwinds, including surging demand, supply chain disruptions, chip shortages, and trade friction which all continue to create challenges. In the longer-term the growing importance of a carbon neutral society and the transition to electric vehicles present significant opportunities for industry.
Looking back on 2020, the initial recovery in China was followed by North America in the second half of the year, with Europe starting its recovery at the end of the period:
Looking ahead, the global economy is projected to grow +6% in 2021 and +4.5% in 2022. This edition of WR forecasts that global robot installations will rebound strongly by +13% to 435,000 units in 2021 driven by deferred investments from 2020, the growing need for resilient supply chains and in order to support capacity expansions. The “boom after the crisis” is expected to moderate in 2022 on a global level. From 2021 to 2024, we can expect average annual growth rates in the medium single-digit range. The mark of 500,000 units installed per year worldwide is expected to be reached in 2024.
We are seeing a long-term transformation across all sectors. Robots continue to move beyond traditional manufacturing into logistics and warehouses, laboratories, workshops, and small production environments. New sectors of the economy, including small and medium size enterprises (SMEs), are embracing automation for the first time and new customer segments (including healthcare, fast moving consumer goods, retail, construction, logistics) are accelerating. There is growing recognition that the scalability of robots and their potential to reduce costs and waste, while enhancing productivity and quality, is helping support job creation in SMEs.
The ‘new normal’ in many industries is mass customization, producing smaller lots of greater variety in shorter product life cycles. The shift towards high mix, low volume production in shorter cycles raises the importance of manufacturing flexibility and agility. Additionally, sustainability is increasingly important for customers, their consumers, and employees. Sustainability and the environment are expected to be major catalysts for accelerating investment in robotics. Automation has a clear role supporting the development of a smarter, better world, enabling sustainable profit, people, and planet.
Technology developments such as the Internet of Things, AI, machine learning and the expanded possibilities offered by 5G are transforming manufacturing, with a growing number of companies embracing them. Through machine learning and AI we see opportunities to further develop human-robot collaboration and to make robots more autonomous, within set parameters. In the future, machine learning and AI will enable robots to self-learn and self-adjust, enabling improved performance with less need for human intervention.
This is the decade where robotics and automation will enable the transformation businesses need. This is the decade where robotics and automation will change the way we work and create a world where people work side-by-side with advanced robots, collaborating on complex tasks, improving the nature of work and helping to advance society. This is the decade when we will fully harness the power of robotics, to unlock growth in new sectors of the economy and when we make work more rewarding, safer, healthier – and more productive for people.
This is an exciting time to be in our industry!
Picture: BlueBotics mini™ mobile robots in operation at ABB’s semiconductor manufacturing plant in Lenzburg, Switzerland © ABB
If you are in Europe and work with, or plan to invest, in automated guided vehicles (AGVs), you might have heard of VDA 5050. Especially if you are involved in the automotive sector. So, what is this standard? And how might it affect future AGV fleet operations? Below is our quick starter guide.
VDA 5050 is a standardized interface for AGV communication. Specifically, this standard concerns the communication between AGVs (often called Fahrerloser Transportsysteme/Transportfahrzeuge (FTS) in Germany) and a master control (in other words, a fleet management software program).
Today, there are many different AGV manufacturers offering vehicles to the market. But, typically, these AGVs only work with their manufacturer’s own specific fleet management software. As soon as a customer requires AGVs from two or more different suppliers, this results in serious challenges, including:
Customers, however, want more. They are increasingly demanding that a fleet management solution should be capable of running a large and, more importantly, diverse fleet of AGVs – whatever the vehicle type or brand.
BlueBotics’ ANT® server software already enables the management of a diverse fleet of ANT® driven vehicles, no matter what the vehicle type (tractor, forklift, underride, etc.) or brand – provided these AGVs are built upon our ANT® lite+ navigation solution. VDA 5050 intends to provide a more generic version of this functionality, which would enable every compliant AGV to work together.
It is the result of a collaboration between the German Association of the Automotive Industry (VDA) and the VDMA Materials handling and Intralogistics Association. These associations are jointly coordinating the VDA 5050 project, which involves the VDA’s AGV user members as well as AGV manufacturer members of the VDMA, including BlueBotics.
VDA 5050 proposes a standard of communication between an AGV fleet manager (software) and any compliant AGVs being operated on-site.
As the VDMA’s website states, the project is about developing “a new interface with which driverless transport systems and control software can communicate with each other independently of manufacturers”.
Since it describes communication between two entities – AGVs and a fleet manager – VDA 5050 will need to be implemented at both ends of this communication channel (i.e., within the fleet manager and within the AGVs themselves) in order to function correctly.
At the time of writing (June 2021), one full version of VDA 5050 has been published, in August 2019, with one revision made to this document in July 2020.
Today’s version (Revision 1.1) covers the act of sending a command to an AGV. Thereafter, the base concept of VDA 5050 is to provide a vehicle with sets of commands, one after another, gradually leading to an entire mission being completed.
ANT® server works differently by providing vehicles with all the data they need upfront. This allows them to be as independent as possible from a site’s WiFi infrastructure – which is not always strong or consistent – during operation.
See ANT® server in action on YouTube.
The current version of VDA 5050 is limited to the communication of commands to AGVs. It does not yet span the many other factors that must be managed to ensure a successful multi-vehicle installation, such as a vehicle’s specific characteristics (e.g., whether it includes a fork, its maximum lift height, the type of pallets it can pick and drop etc.). This deeper level of detail is still to come, most likely in the next two to three years.
VDA 5050 is proposed today as a base standard for discussion and testing. It will evolve over the coming two to five years. However, its final publication date has not been confirmed.
A PDF version is available in English and German from the VDA’s website.
No, it is not only for Germany. It just comes from there.
VDA 5050 was born out of the country’s strong automotive sector, which is today one of the world’s largest users of AGVs. With German car manufacturers being very active worldwide, however, we can expect them to drive this standard not only in Germany but more widely across Europe and possibly across other regions too.
The VDMA is planning to release version 2 of the standard in Q3, 2021.
Please contact Bluebotics on further questions on VDA 5050.
For decades, robots were designed and programmed to perform one task and one task only. If a business ever needed a robot to perform a different task from the one it was programmed to do, it meant taking the robot offline, physically interfacing with the robot, uploading new programming, and booting it back up. This repurposing costs time, labor, and money. It also requires technical skills which are not readily available on the factory floor, meaning businesses may have to hire more specialized employees or pay for trainings. Multiply all this by number of robots on the factory floor, and the potential costs for robots in manufacturing becomes staggering.
But it doesn’t have to be. We live in an age known as the Fourth Industrial Revolution, or Industry 4.0, characterized by smart, adaptable technology. Automation is becoming increasingly, well, automated. In some of the more modern plants, machines are communicating with each other, even sending data to remote locations. Although machine-to-machine communication is not yet mainstream in manufacturing, it’s on its way. All that costly, time-consuming maintenance is being wiped away, saving labor, resources, and money.
Modern industrial robots are more connected, intelligent, and versatile than their predecessors. They can reduce production cycles and optimize asset utilization. Today, manufacturers can start the day with a floor of robots performing one task, then finish the workday with those same robots performing a different set of tasks. This adaptability makes multi-tasking robots very useful in the domain of high-mix, low-volume manufacturing.
A company might hesitate to make their robots programmable, thinking the endeavor involves huge costs and brand-new hardware, but no new hardware is necessary. A factory can outfit its existing robots with a system of low-cost software components to implement multi-tasking. Once installed, robots can be reprogrammed remotely to execute new movements according to the manufacturer's specifications.
You see, robots have controllers that run their programs. These controllers — hardware boxes with embedded computers that run the programs necessary for a specific task — often contain multiple programs which programmers can upload from virtually anywhere. Each program is an aggregation of a series of commands that the programmer packages before uploading. These programs are created using internal or external code editors or even using recordings of the robot's actions. There are 3D simulators which can simulate the robot’s work cell with a high degree of accuracy. Robot programs created using these simulators are called offline programs, and these programs can be directly copied to the physical robots and executed.
The number of tasks robots can execute has also grown. This has been a huge help throughout the coronavirus pandemic. Traditionally, the close proximity of assembly workers would put them at high risk of exposure to an airborne virus. With increased automation and robotics supplementing the human workforce, assembly lines can become less crowded and those risks can be substantially mitigated.
Other advantages include task updates, spotting problems before they start, and knowing precisely when maintenance is due. The same channels used to operate robots remotely can be used to send data from robots to manufacturers. In this way, remote access provides manufacturers with valuable information like job status, aggregated data about parts produced, maintenance, updates, and potential issues — all in real time.
Another advantage of robots' new versatility is greater return on investment. You might have the capital to purchase robots but don't because you are never manufacturing one thing for long, or you manufacture one thing exclusively but fear you might not have an indefinite market. With programmable robots, you can pivot to whatever is most profitable with minimal expense by simply reprogramming existing hardware. This means lower upfront costs, fewer robots, and more space on the factory floor. If you manufacture more than one product, your initial investment will be much lower with industrial multi-tasking robots because you can allocate more than one task to a robot, meaning fewer robots overall. Multi-tasking robots may also decrease the number of robot operations personnel needed to keep robots in production.
It used to be that businesses wondered if they could afford robots. But with robots now capable of performing more tasks more efficiently, the initial investment dropping, and a global pandemic demanding more space between employees, how can you afford not to?
Wipro offers industrial robotics with smart warehousing and smart manufacturing that can be deployed almost anywhere globally, not just in major regions.
Image © Wipro
Robots are on the move! Autonomous mobile robots are changing how work is done in a number of industry sectors, with health and other benefits for companies and employees.
For decades, robots have been largely stationary. Now, however, robots are able to move around autonomously, navigating according to an internal map which can be updated in real-time. These Autonomous Mobile Robots (AMRs) can respond to unexpected objects in their path, either slowing, or stopping as appropriate. They can replan their route in response to obstacles, generally with the help of fleet management systems that coordinate and monitor the activity of multiple AMRs.
AMRs spare employees tedious fetching and carrying of goods, and heavy lifting, in industries as diverse as logistics and healthcare. They improve efficiency and reduce waste in manufacturing by connecting different parts of the production process.
A Mobile Revolution: How mobility is reshaping robotics, a new paper from the International Federation of Robotics, provides an in-depth view of how AMRs are reshaping manufacturing, logistics, healthcare, retail, and public environments. Below are the highlights.
AMRs help manufacturers to rapidly adjust production to meet demand. This is particularly important for manufacturers producing a small number of many different products (high-mix / low volume production). These companies need to reorganize production lines frequently - often at short notice- and AMRs give them greater flexibility. Danish manufacturer VOLA, for example, implemented a fleet of mobile robots to move boxes of products from one location to another, replacing traditional conveyors. This means VOLA can easily reconfigure the factory layout whenever necessary.
Please see video on YouTube: Flexible production at VOLA thanks to AMRs
AMRs equipped with vision systems are also used for quality inspection. Inspecting parts at each stage of production, or during transport from one stage to the next, rather than at the end, saves costs as manufacturers can reject faulty parts before they have been worked on further.
The logistics sector has led the boom in AMRs. According to the IFR’s Word Robotics Service Robots report, unit sales of logistics robots increased six-fold between 2014 and 2019, and the IFR predicts average annual growth in unit sales of 31% between 2020 and 2023. AMRs are mostly used for transporting goods throughout a warehouse, reducing the time employees spend fetching and carrying. Wärtsilä Global Logistics Services and DHL saved employees more than 30 extra kilometers a day by using AMRs to fetch and carry goods.
Please see video on YouTube: AMRs at Wärtsilä
While Automated Guided Vehicles that follow fixed tracks have been used for some time in hospital basements, carrying linens and medications, AMRs are now navigating around hospital floors, delivering linens and medicines to nurse stations on the ward. Many can operate lifts and doors. Nurses spend a significant amount of time fetching and carrying medications, linen and waste, walking at least 4 miles per day according to one study. Robots can significantly reduce this, giving nurses more time to focus on patient care.
AMRs are also helping to make hospitals even safer. Autonomous cleaning and disinfection robots are widely used in hospitals and sales of disinfection robots that kill germs with UV light boomed during the COVID-19 pandemic. Some AMRs with robotic arms are able to carry out simply diagnostics – such as taking a patient’s temperature – reducing contact while medical staff determine whether a patient may have a highly infectious disease.
Please see video on YouTube: Telepresence robots connect specialist consultants with their patients
Telepresence robots - AMRs with video screens – are connecting doctors with patients, enabling medical staff to quickly connect with specialist consultants. Dignity Health began using telepresence robots to quickly diagnose stroke patients and now uses the machines in emergency and intensive care units at most of its 32 California hospitals. As one doctor in this video commented, “ No longer does distance affect a person’s ability to access the best care possible.”
AMRs are making life easier for retail staff and shoppers. They are used in warehouses to transport goods, and are increasingly used in store fronts for stock-taking, ensuring products are available and giving staff more time to focus on customers. Walmart is trialling stock-taking robots that operate while customers are in the store. AMRs are also used to provide information via touchscreen to customers on product location or to connect customers with service agents via a video.
Please see video on YouTube: AMRs reduce the time needed for stocktaking at Decathlon Singapore
AMRs have an increasingly wide application in public environments such as airports, hotels and shopping malls. For example, robots can deliver room service orders in hotels – a practice adopted by a number of COVID-19 quarantine hotels.
Please see video on YouTube: Savioke’s Relay Robot delivers room service
They are also providing information on gate locations and flight schedules to passengers in airports, and accompanying passengers to their gate.
Research in various mobile robot technologies is proceeding at a rapid pace. With the help of vision technologies and artificial intelligence algorithms, AMRs will increasingly be able to better understand what they are seeing, and to respond appropriately, for example to an elderly person or a child. Improvements in natural language processing will enable AMRs to interact more easily with employees, patients and residents in rehabilitation and care facilities, and the public.
Most AMRs today consist of either or a mobile platform, or a complete closed system – such as room service and telepresence robots. In future, mobile robot arms attached to an AMR will give companies in different industry sectors even greater flexibility. In manufacturing, for example, AMRs with robot arms will move to different production cells and perform different tasks at them.
ABB is trialling the use of this functionality to automate repetitive and time-consuming laboratory work such preparation of medicines, loading and unloading centrifuges, pipetting and handling liquids, and picking up and sorting test tubes, freeing medical staff and lab workers from repetitive and time-consuming tasks, improving the accuracy of laboratory work and ultimately enhancing patient satisfaction and safety.
Welcome to the mobile revolution!
Teaser image: © PAL Robotics
Robot programming accounts for a significant portion of the overall cost of robot adoption and has traditionally required programmers trained in frameworks specific to each robot manufacturer.
This is changing, with rapid developments in model-based approaches, the ‘appification’ of robot programming, and demonstration teaching methods. We look at recent trends in robot programming and the implications for robot adoption and skills requirements.
Model-based development - already well-established in software engineering and widely used in manufacturing sectors such as automotive and avionics- is now increasingly adopted in robotics. One model-based approach encapsulates the code that describes specific attributes and actions of the robot in blocks. Blocks can describe the physical structure of the robot, the activities or ‘skills’ it should perform, its components such as sensors and actuators, as well as the interface between the robot program and other controllers such as actuators or other machines. These blocks can then be combined in different ways to create new programs, without writing each line of code from scratch. Robots can be programmed faster, and by generalist engineers or, for simple applications, production operators. Experts estimate that model-based programming through graphical user interfaces aimed at non-programmers can save up to 75% of installation time and cost.
Model-based development approaches are offered by a number of robot manufacturers for their robot fleets. There are also start-ups providing libraries of models with easy-to-use application-building interfaces that do not require programming skills. One example is drag&bot, a spin-off of Germany’s Fraunhofer Institute. The company provides a graphical user interface through which peripherals such as cameras, actuators such as grippers and programmable line controllers from a range of manufacturers can be integrated with different robots. Drag&bot also provides models for common functions such as palletizing, and support in customizing more complex applications such as pick-and-place, using existing models.
Many companies have installed robots from different manufacturers and want to be able to reuse an application developed for one robot operating system on a robot from a different manufacturer. This has traditionally required significant reprogramming. A number of initiatives are focused on enabling greater reusability of model-based programs. This reduces the resources needed to make specific blocks of code usable on a new robot and in turn lowers the overall implementation cost and increases the economic viability of automating new processes. Traditionally, industrial robots have been used to automate processes that remain constant across large numbers of robots over time – for example welding and cutting parts in automotive manufacturing. However, as manufacturers come under increasing pressure to adapt production to smaller runs of a larger variety of products (high-mix/low-volume), the ability to cost-effectively adapt existing applications and automate new processes becomes a competitive advantage.
The ROS-Industrial Consortium aims to support reusability by building on the open-source framework ROS (Robot Operating System) - a collection of tools, libraries, and conventions for robot programming heavily used by robot developers but not yet widely accepted for use in commercial applications, particularly for industrial robots as there are still concerns regarding support for the strict real-time requirements that are a feature of most industrial robot applications, functional safety and liability. ROS 2, a major revision of the ROS programming framework, aims to address these issues, though the required software libraries are still in development. ROS-Industrial Consortium members, which include a number of industrial robot manufacturers such as ABB, Yaskawa and Universal Robots, contribute code or programming frameworks, which enable re-use of specific blocks of existing proprietary code. The ROS-Industrial repository includes interfaces for common industrial manipulators, grippers, sensors, and device networks as well as software libraries for tasks such as automatic 2D/3D sensor calibration and process path/motion planning.
In an ideal world, full robot applications would be available for download through an App Store with no further need for customization - as we’re used to with our cell phones and computers. This is not realistic in robotics, given that robots interact with their external environment, which varies from company to company. Service robots that work in public environments are subject to high levels of unpredictability in the external environment which would be impossible to model in a ‘plug-and-play’ app.
Please see Xito platform success story: Transpharm Logistik /Teva – on YouTube.
However, the developments described above are a move in the direction of the ‘appification’ of robotics. Some robot manufacturers and providers of robot actuators are working toward ‘out-of-the-box’ applications for simple tasks such as tightening screws and sanding (for example, OnRobot’s sanding application).
Another development supporting reusability is the application marketplace through which companies and systems integrators can find and access existing robot programming models and expertise to reduce programming time. One example is Xito, which emerged from the European Union’s RobMoSys project. Xito enables end users, system integrators and robot manufacturers to provide and find existing pre-programmed models for robot functions and interfaces, or to connect with a developer with most expertise in the specific requirement for custom development. End-users or system integrators describe the intended application and the platform suggests the most suitable components and model-building interface. End-users with a basic engineering degree can program robotic applications, lowering the cost of automation. Xito is focused on the fast-moving service robot market, characterized by a high number of specialist companies. These companies benefit from end-users being able to combine their solutions rapidly and cost-effectively with solutions from other providers to form a complete robotic application.
Demonstration teaching, in which the user guides the robot arm through the path of motion to be followed – with small adjustments then made through a user interface - is common in ‘cobots’ which are often used alongside human workers in environments where tasks vary frequently. Demonstration teaching can be done by a production operator, significantly lowering the cost of automation for manufacturers in high-mix/low-volume environments.
A new start-up, Wandelbots, provides a demonstration teaching interface that automatically converts the demonstration path mapped by the production operator to code for robots from different manufacturers to enable reusability.
Demonstration teaching is not typically used for programming industrial robot applications requiring a very high degree of precision and speed, though this may change in the future. Please see example on YouTube with a KUKA robot.
As model-based approaches mature, we can expect to see de-facto standards emerge from the most popular models. This will further simplify implementation and reusability. As standards become ubiquitous and robust, they can be used for certification, making it easier for developers to offer, and end-users to find, trusted application building blocks. We may also see the increased use of model-based approaches for simulation. Simulation enables end-users to test an application to explore usability and return on investment before having to incur costs. However, it has historically been difficult to do for robots that are influenced by variable or unpredictable external conditions.
In general, advances in model-based robot programming have huge potential for reducing the cost of installation of robots, particularly for high-mix/low-volume production environments and service-robot applications. By lowering the barrier to entry in terms of costs and required skills, model-based approaches are critical to accelerating robot adoption and have a promising future.
Robots have been in use in the healthcare sector for some time, operating largely behind the scenes. Over the last five years, the range of robotic applications in healthcare has expanded rapidly to include assistive applications for doctors, nurses, caregivers and patients in hospitals and care facilities. In the second of this two-part blog series, we focus on applications in which robots come into direct contact with both healthcare staff and patients, keeping hospitals safe, and assisting doctors and nurses in a range of functions.
According to the World Health Organisation, the cost of treating hospital infections runs to around €7 billion per year in Europe and US$6.5 billion in the U.S. Cleaning and disinfection robots have been at work reducing this toll for some time. However, the COVID-19 pandemic has brought them into the spotlight, increased adoption, and also expanded use outside of hospitals to public spaces such as public transport and shopping malls. Over 30 disinfection robot types from different manufacturers were newly registered in 2020 and the IFR expects double-digit growth in this market in the coming years. Many mobile disinfection robots use UV light to kill germs and most can be operated easily by cleaning staff. Ultra-violet disinfection robots can destroy 99.9% of all microorganisms in a hospital room within 10 minutes. Others spray chemical disinfectants. See examples here.
Robots have been used for some time for minimally-invasive surgery, allowing surgeons to perform a variety of operations with greater precision and faster recovery times for patients. The range of existing systems is continuously expanding. For example, Swiss company AOT recently announced a new robot application for bone surgery, using a KUKA robot. The market for surgical robots is niche in terms of unit sales but accounted for over US$ 5 billion in 2019 due to the high price of these robots. The IFR expects an annual sales growth of 23% between 2020 and 2023.
Precision work through robot-guided laser ablation © image AOT AG
Robots are also used increasingly in patient rehabilitation. The advantage of robot devices over rehabilitation exercises guided only by a therapist is that the robot device ensures that the movement is repeated in the same way each time, training the brain to enable muscles to carry out the movements alone. Repetitions per session are also generally higher with robot-assisted rehabilitation. The robots collect data on the patient’s performance, enabling therapists and doctors to assess progress accurately. Most rehabilitation robots consist of an exoskeleton that the patient wears, and other equipment such as a treadmill or computer screen guiding the exercises. See examples here.
KUKA’s ROBERT® rehab robot, image credit KUKA
The market for assistance robots in healthcare is relatively young but shows promise. These robots can provide information, respond to simple questions and in some cases, connect the user with a trained professional via video link, enabling remote communication between doctors, nurses and patients. For example, mobile bases equipped with computer screens can follow nurses or navigate autonomously to a patient’s bed to connect the patient with a doctor at a remote location. This not only allows for far more effective specialist consultations – since the doctor can see and interact with the patient rather than work off patient notes – it also enables medical interaction with patients who may be highly infectious. Some hospitals use a mobile robot base equipped with a robot arm to take simple diagnostic measurements such as a patient’s temperature – an application that became more prevalent during the COVID-19 pandemic.
There is a growing market for these telepresence robots as part of efforts to help elderly people remain in assisted living or their homes for longer, staying connected to their caregivers, friends and family.
A cardiologist discusses the advantages of using a telepresence robot
The image of the remote user is displayed on the screen and the robot can be driven around to view anything in its vicinity. Most of these robots are controllable from any location with a smartphone or computer and internet connection. Family members, friends, doctors, and caregivers can all log into the telepresence robot, drive it, interact with others, and explore the environment with audio and video. See examples here.
The IFR predicts strong growth of 40% per year in unit sales of mobile guidance, information and telepresence robots between 2020 and 2023 across a range of industry sectors. However, adoption rates in the healthcare sector are likely to be somewhat lower, due to budget constraints in the sector and also strict regulation governing the care and data privacy of patients and vulnerable citizens such as the elderly.
As the range of tasks performed by both collaborative and mobile robots increases, we can expect to see increased adoption of robots across the entire spectrum of healthcare. In the short to medium-term, we can expect an expansion of robots for tasks that do not involve significant interaction with physicians, nurses and patients – such as fetching and carrying materials and medications. In the long term, as software algorithms develop, we will see increasing robot-to-human interaction. For example, development is going into intelligent assistants for care homes checking if someone has water to drink and serving them if not, as well as providing entertainment and assisting carers. These kinds of tasks require complex software algorithms in order for robots to understand and respond appropriately to the environment. However, these applications are technically highly complex and the regulatory and budgetary constraints faced by most healthcare organisations mean that it will likely be decades before we see widespread adoption of advanced intelligent assistants in healthcare. We may also see nurses equipped with exoskeletons, helping them to move patients while avoiding back strain. In addition to budgetary considerations, however, exoskeletons currently take time to put on and set-up so it will be some time before exoskeletons become commercial reality in hospitals.
Please read also the IFR Information Paper on Robots in Daily Life - the positive impact of robots on wellbeing.
Korea is a ‘Top 5’ manufacturing powerhouse in all the main manufacturing sectors including automotive, semiconductor, electronics, machinery, and chemicals. Demand from this solid manufacturing foundation has enabled Korea to become a leading player in robotics, ranking consistently among the top 2 in robot density. The size of the Korean market has also made it very attractive to global robotics companies.
Despite such a strong foundation, Korean robot manufacturers have had a very weak presence not only in the global market, but also the domestic market until now. Recently, however, these companies went through a massive transformation, and are now at the center of attention in the global market.
Below, I discuss the changes taking place in Korea, and the impact they may have on the global market. There are 5 emerging trends:
1. Large enterprises have started to focus on robotics as a key future growth engine
In the past, the most active robot manufacturers in Korea were small and medium-sized enterprises. However, large enterprises such as Samsung, LG, Hyundai, Doosan, Hanwha, and KT have recently announced that they will be focusing on the robotics business as a future source of growth, drawing attention to the growth potential of the robotics sector.
Samsung’s vision for next-generation service robots
There are three main things to note regarding these large enterprises’ drive to build a presence in the robotics industry:
Doosan’s plans for industrial robots
2. The robot venture ecosystem is becoming more diverse, with an increasing stock of domestic success stories
There are two main types of robotics venture in Korea:
These ventures are growing rapidly with heightened interest from both customers and capital markets.
Cobot maker Rainbow Robotics is a leading example of a domestic OEM venture, proving its potential by successfully going public in the KOSDAQ market last February. Their revenue in 2020 was only KRW 5.4 billion, but the company was valued to be worth over KRW 500 billion right after listing and is currently at the center of attention in the market. Other cobot OEMs such as Neuromeca, and autonomous driving-enabled logistics robot manufacturers such as Twinny are also planning to go public, so there is high expectation that there will be more success stories to come.
Service providers are ventures that are utilizing robots to bring innovation to their existing business operations. The companies which are making their mark this way are mostly food tech companies, such as Lounge X, which is famous for its barista robot, and Robert Chicken, and DDeck which are famous for chicken-frying robots. These companies are taking note of the failures of the first generation of robotic food tech ventures in Silicon Valley and achieving rapid growing by advancing their service and operations on a sustainable foundation.
3. There is a significant jump in robot implementation by manufacturing SMEs
In Korea, robots were mostly used by large and medium-sized enterprises in the manufacturing space. Nowadays, however, more small-to-medium-sized companies (SMEs) in this sector are implementing robotic solutions, as they have become more user-friendly and cost-competitive. Recently, a semiconductor equipment supplier installed 77 domestic cobots and was able to improve their productivity by 50% as a result. In the past, only large enterprises could afford to implement robots at this scale, so this increase in accessibility may prove to be a turning point for the industry.
4. Creativity in the Korean robotics industry: Unique applications in the service sector
The unbridled creativity of the Korean people is taking over the world not only through K-Pop, but also through innovative robotic applications! Here are some examples:
Fried chicken is one of Korea’s most beloved foods and chicken-frying robot solutions developed by food tech ventures are growing fast.
A restaurant chain with 10 stores fully automated their beverage-making and serving process
A food service robot specifically designed to work in gaming cafes, the most common destination for youngsters who want to take a break
Such applications are no longer being released simply as headline-grabbing marketing ploys. Rather, they are applied in actual business operations to improve efficiency. The application of creativity and technology means these kinds of applications are being developed at a rapid pace in many areas.
5. The Korean government - a strong and reliable partner of Korean robots
As mentioned above, there is clear momentum in the domestic robotics ecosystem. However, realistically, there is still a long way to go for Korean robots to be competitive at the global level.
The Korean government has established institutions such as KIRIA (Korea institute for Robot industry Advancement) and KAR (Korea Association of Robot industry) to provide systematic support. These two institutions oversee the development and distribution of the domestic robotics industry. In addition, they are responsible for establishing required policies based on current market trends from both the provider and end-user’s perspective, including:
The above examples of new applications were able to see the light of day because of such ample government support which allowed the companies to take on risks.
Note: The opinions expressed in this blog are those of the author and do not reflect the position of, or data from, the IFR
Picture © Hyundai Rotem
Robots have been in use in the healthcare sector for some time, operating largely behind the scenes. Over the last five years, the range of robotic applications in healthcare has expanded rapidly to include assistive applications for doctors, nurses, caregivers and patients in hospitals and care facilities.
In the first of a two-part series, this blog will look at robot applications in drug development and production, drug dispensing in pharmacies and hospital logistics.
Robots are in use across the whole pharmaceutical supply chain, from basic research to the production of medicines, quality inspection and packaging. Robots support the discovery of vital new treatments; enable faster medical tests for patients; help pharmaceutical manufacturers to meet increasingly strict regulations for the production of medicines and maximise the efficiency of drug production.
Since industrial robots have their origin in manufacturing sectors, it’s no surprise that they are most established in the manufacturing phase of the drug development lifecycle. The technologies needed for performing repetitive tasks with high degrees of precision and accuracy are already mature. The main focus of robots in the manufacturing process is at the filling, assembly and packaging stage, where tasks include filling and labelling containers, assembling finished products such as syringes and packaging assembled products.
For example, industrial robots are used for the assembly of medical syringes (FANUC/Farason) or for filling and closing of vials (Stäubli/Zellwag Pharmatech).
FANUC robots were used by system integrator Farason Corporation in a medical syringe assembly system.
While the applications themselves are well-established, the specifications for robots used in pharmaceutical and medical applications are often much tighter than those for other industries. Working in clean-rooms or sterile environments, for example, requires special filtration and ventilation system to protect against the emission of gases and particles. Clean-room robots often have a stainless-steel finish without paint, to prevent adherence of dust and dirt and allow for proper cleaning and sterilization.
Using robots in laboratories for drug development as well as for testing is less well established but this is changing. Robots in laboratories free scientists and laboratory technicians from tedious, repetitive tasks such as pipetting and vial filling, giving them more time to focus on science, and protecting them from repetitive strain injuries.
Most research laboratories are not automated, and the range and shorter runs of procedures in smaller laboratories means robots have not yet proved cost-effective. This is changing, particularly with the rise of cobots able to work alongside humans as well as dual-armed robots able to perform a variety of tasks – for example, a dual-armed robot performing a variety of tasks in a biomedical cell.
Robots are already more established in hospital laboratories with large throughput of tests. For example, Copenhagen University Hospital (video) was able to maintain a response rate of delivering 90% of all results within the hour despite a 20% increase in blood samples, due to the adoption of collaborative robots. Also traditional industrial robots can be used for the automated sorting of blood samples, as shown by Aalborg University Hospital.
Pharmacy dispensing is a relatively new application for robotics but has a promising future. Robots improve the efficiency and – vitally – the accuracy of drug dispensing in pharmacies. Medication errors, which include dispensing errors, account for cost US$42bn worldwide (IMS Institute for Healthcare Informatics). The British Wirral University Teaching Hospital, for example, reported a 50 percent reduction of dispensing errors in the four months after implementing a pharmacy robot (Journal of mHealth).
Robots are used in both hospital and community pharmacies that deliver medications ordered online. For example, the Shanghai Seventh People’s hospital uses two robots to automate dispensing. One robot locates the medicines in the prescription, which is entered online, while the second assembles the medications in a basket for each order.
ABB pharmacy dispensing robots at the Shanghai Seventh People’s hospital.
Going forward, we can expect to see advances in grippers supporting more applications involving handling of delicate materials in laboratories and packaging. We may also see increasing adoption of robotic vision technologies for quality inspection and tracking. Vision technologies are widely used in the pharmaceutical industry but are typically not mounted onto the robot. While robots in the applications described above are almost exclusively static, we are seeing the start of applications combining a mobile base and robot arm, which allows the robot to perform sequential tasks that involve moving from one machine to another. ABB is prototyping this concept at the Texas Medical Center for example.
Though autonomous mobile robots (AMRs) have been used for some time in hospitals to transport linens, medication and medical equipment, this still is a relatively immature market as many hospitals operate under tight budgetary constraints and have not yet turned to automation. A shortage of healthcare workers in many countries is likely to spur adoption. The boom in AMR manufacturers combined with increasing maturity and cost-effectiveness of the component technologies and assistive tools for installation is likely to reduce the overall cost of installation, further spurring uptake.
In a typical 200-bed hospital, equipment and waste is transported just under 400 miles per week. It is estimated that the use of AMRs reduces the cost per delivery by 50-80% and reduces the average distance of 3-4 miles that a nurse walks each day. These robots reduce back injuries from lifting in hospital personnel and give nurses more time to concentrate on patient care.
To work in hospitals and care facilities, AMRs need to negotiate elevators, and some can issue simple voice commands to alert people to their approach. For example, Zealand University Hospital in Denmark uses an AMR to transport goods from the hospital’s sterilization center. The robot travels more than 10 kilometers per week, improving service, minimizing storage space, reducing walking time for personnel, and preventing equipment shortages.
Going forward, we will need developments in standards for interaction with hardware such as elevators and doors. Communications protocols will reduce overall cost of implementation by enabling faster integration.
In global comparison, some countries are further ahead than others when it comes to the testing and deployment of new technologies in the healthcare sector. There is a discrepancy between companies in the private sector, that usually are driven by competition and the need for high productivity, while publicly-funded undertakings like hospitals are often working on tight budgets and the return on invest for longer-term investments into technology is not yet in the focus.
While in the examples shown so far, the robots mostly are either operating in isolation or interact preferably with trained personnel, AMRs and other types of service robots in healthcare are starting to be used for applications in which the robot has direct contact with patients. Part 2 of this blog will focus on the latter applications.
Please read also the IFR Information Paper on Robots in Daily Life - the positive impact of robots on wellbeing.
Teaser picture: ABB pharmacy dispensing robots at the Shanghai Seventh People’s hospital © ABB
We spoke with IFR members to hear their views on the most promising trends in robots. Here’s what we heard.
Rapid developments in 3D vision systems and software algorithms are increasing the range of tasks robots are able to perform autonomously. One example is bin picking, a complex operation which requires a robot to be able to identify and pick a single part out of a bin of either similar or dissimilar parts. The target part may be entirely or partially covered by others. Once the part has been found, the robot’s software processes data to determine how to reach it, calculating the proper orientation for the effector (hand or other gripping mechanism). Sensors in the gripper feed data to the robot’s software that sends code back to the robot to enable it to pick up the object without damaging it by either exerting too much pressure, or too little so that the object slips.
Over the next 10 years, robots will increasingly be able to assess and respond appropriately to their environment, thanks to developments in semantic intelligence. For example, the robot will recognise whether an object in front of it is a human or a machine. It will be able to recognise the person’s intended move – for example heading towards a door - and will then replan its path accordingly. We can also expect to see further developments in speech and gesture recognition, enabling robots to respond appropriately to workers and the general public. It’s important to note that while robots will increasingly be able to make their own decisions on how best to perform a certain task, a hard-coded layer of instructions – such as stop if any object is nearer than 10cm – will always take precedence, ensuring human safety.
Manufacturers and logistics providers are under increasing pressure to produce and ship smaller, customized orders in short timeframes. Many are automating the production process to be able to respond more efficiently to new orders. Some are also restructuring production and logistics, moving from linear production and logistics lines to a series of standard production cells which can be rapidly reconfigured to the task at hand. Automotive manufacturers are the major driving force behind these trends, but we can expect adoption in other manufacturing and logistics sectors in the future as well.
As we note in our recent information paper, ‘How Connected Robots are Transforming Manufacturing’, manufacturers are automating production lines by connecting the machines – including robots – to each other and to software such as computer aided design and enterprise resource planning systems. The production process can be automatically triggered by a completed product design, or an order entry.
In such a non-linear production layout, a collection of small production cells can be rapidly reconfigured to perform parts of a production process. Autonomous mobile robots carry materials and parts between the cells and can activate the machines in the cells as well as carry out some tasks themselves. Using 3D vision software, mobile robots will in the future be able to run quality control checks on parts as they transport them, ensuring quality control is done on the fly versus at the end of the run, minimising waste and reducing costs. In logistics, autonomous mobile robots and other machines such as autonomous forklifts transport goods through the packaging process, and picking robots select and pack goods from conveyors.
A combination of the new functionality described above and lower set-up costs are driving robot adoption in industry sectors and smaller companies that have not yet automated.
In addition to a boom in logistics robots, the IFR tracks increased robot adoption in manufacturing sectors such as food production and pharmaceuticals, as well as adoption in service sectors such as healthcare and retail.
Small and mid-sized manufacturers (SMEs) form the backbone of most manufacturing economies, but many have been slow to automate. A number of developments are changing this. First, robots are now easier to program and re-task, throught intuitive interfaces and demonstration. Second, the new generation of collaborative robots can easily be integrated into existing production processes alongside workers – versus replanning the whole production line for automation. Finally, Robots as a Service business models, in which companies lease rather than buy a robot, remove the need for initial capital outlay, making it even more attractive for smaller manufacturers to take the initial step towards robotization.
The US-China trade war, the COVID-19 pandemic and Brexit have all raised awareness of the rigid nature of global supply chains. Robots enable manufacturers to build resilience into their supply chains. For example, collaborative robots that work alongside humans and can be quickly re-tasked can be used to enable production in peak order periods, when most manufacturers find it difficult to ramp up staff. Robots also assist in meeting social distancing requirements in factories. Finally, robot adoption makes local production a more viable option economically, giving manufacturers in developed economies greater flexibility in adjusting supply chains in response to global shocks.
Robots contribute to lowering the overall carbon footprint of manufacturing by minimising material waste and enabling manufacturers to optimise space – and thus the energy associated with lighting and heating. As noted above, robots are an enabler of shorter supply chains which can contribute to a lower footprint. Robots are also themselves increasingly energy efficient. For example, they are increasingly made from lighter, composite materials and using energy-efficient engines and gears with reduced frictional losses. Many have energy-saving modes when in stand-by, as well as energy-efficient control and drive technologies. Improved motion path planning and mapping of acceleration and motion to the required tact time also reduces the energy needed to execute tasks. The end of service life also is increasingly in the focus. Robots typically have long lifespans, which can be even extended nowadays, and after that, refurbishing and recycling are two options.
Picture: © OMRON
Only a couple of years ago, headlines were dominated by the narrative that automation was coming after jobs in a wide range of industry sectors. Today, there is increasing recognition that automation will change jobs, but eliminate only a small percentage. The challenge is not mass unemployment, but how to ensure today and tomorrow’s workforce is equipped with the skills to work with new technologies.
This challenge was the topic of a recent virtual executive roundtable discussion hosted by the IFR together with Messe München and is also the focus of a new positioning paper by the IFR, ‘Next Generation Skills: Enabling Today’s and Tomorrow’s Workforce to Benefit from Automation’
Skills shortages are already a challenge in sectors such as manufacturing that shed jobs around 10 years ago and have struggled to keep pace with current demand. In the US, for example, Department of Labor figures from January 2020 showed nearly 80% of manufacturers struggling to fill over 400,000 open positions. One third were forced to turn down new business in 2019 due to a skills shortage, according to the National Association of Manufacturers.
As the ‘baby boomer’ generation (born between 1954 and 1964) retires, there will be an acute shortage of ‘classic’ manufacturing skills such as welding, machine operators and assembly workers. Cedefop, the European Centre for the Development of Vocational Training, forecasts that 91% of new hires in Europe to 2030 will replace retiring workers, meaning manufacturers will have to replace traditional skills at the same time as introducing new skills required to manage and reap the benefits of automation technology.
What will those new skills be? The IFR surveyed members and reviewed the literature to explore how automation, and specifically robotics, will change the skills requirements of four main manufacturing job profiles – production worker; technician; engineer and production manager. We found that all four job profiles can expect significant interaction with robotic and other automation technologies. IFR members estimate that over 50% of production operators will be working with robots in 10 years’ time. Robots will assist workers in tedious, unergonomic work such as feeding machines, lifting and holding heavy parts and performing repetitive tasks that require high degrees of precision such as applying glue or polishing surfaces. Many operators will learn to program and supervise robots. Technicians will need broad information technology skills to use data generated by machines, and analytic tools, to assess when machines need maintenance. They will also start to take a proactive role in process optimization. Engineers will increasingly manage connected systems rather than discrete machines and will need expertise in electronics and software as well as traditional skills in mechanical engineering. Production managers will oversee a broader range of machines and processes than in the past, requiring broad technology skills in related systems such as enterprise resource planning (ERP). They will also perform complex optimization tasks across the entire production line. In general, manufacturers will place higher value on human skills such as critical thinking, problem-solving, and people management. For many manufacturers, this will entail a shift in corporate culture, with flatter organizational hierarchies and more autonomy for agile teams working locally and remotely. Increasing robot adoption will also create new jobs, such as the Smart Factory Manager, Robot Teaming Coordinator and Robot Debugger (see the paper for job descriptions and more examples).
How will employees acquire these new skills? This was the main focus of the IFR executive roundtable. Panelists agreed that workers must be central to automation strategies, and that effective skills training requires the close collaboration of an eco-system of actors including robot manufacturers, employers in manufacturing and other industry sectors, education institutes, trade unions and government. The group stressed the urgency of coordinated action. As Mike Cicco, President & CEO of FANUC America put it, ‘Unless we prepare the manufacturing industry for the factory worker of the future, we’ll lose skilled labor, which is already reduced due to demographic change’.
The group agreed that different programs are needed for future and existing workers. More needs to be done in primary and secondary education to interest young people in sciences and automation technologies in order to develop the next generation of manufacturing workers and automation specialists in other sectors. Felix Rohn, Policy Officer at European Commission’s Directorate-General for Employment, Social Affairs & Inclusion, pointed to the example of Poland, which made the study of natural sciences and maths mandatory up to the last two years of secondary school education, resulting in a significant increase in the number of science students in higher education. Jeff Burnstein, President of the US Robotics Industries Association, pointed to the First Robotics program which organizes a variety of technology competitions for school students of different ages to introduce and interest them in new technologies, including robotics.
Anna Byhovskaya, Senior Policy Advisor of The Trade Union Advisory Committee to the OECD (TUAC) pointed to the difficulties in re-skilling low-skilled workers. ‘Low-skilled workers are not use to receiving training and often aren’t given a financial incentive. We need to get employers to work with trade unions to encourage uptake of training, ensure the right financial mechanisms are in place, as well as time off for training. We already see a correlation between collective bargaining coverage and willingness to take up training by employers.’ Felix Rohn commented that the European Union is exploring individual learning accounts which are already in place in France. Jeff Burnstein and Mike Cicco pointed out that technologies such as virtual reality and increasingly intuitive robot programming interfaces are already reducing the time needed by people without a technical background to use robots.
The group agreed that the most important factor in ensuring successful up- and re-skilling is effective collaboration between different actors, with clear responsibilities. Robot manufacturers should be responsible for advising on the skills required to use their equipment, as well as ensuring robots are available in colleges and training centers and that trainers are up to speed with the latest technology developments. Companies must ensure workers are given time for training and collaborate with trade unions to ensure access to and uptake of training programs. Education institutes must work with both robot manufacturers and employers to develop curricula based around the latest technology and adapted to the needs of employees. Government must provide the right incentives for these activities and drive collaboration between partners. Parents also have a role in enabling a cultural shift that recognizes technical apprenticeships as positive career paths for young people.
The panel agreed there is already best practice that can be scaled and adopted in other geographies. Felix Rohn pointed to the Dutch government’s ‘Triple Helix’ model of cooperation at regional level between regional government, education and training providers and trade unions. He also mentioned the European Commission’s ‘Pact for Skills’, whose signatories from both public and private sector commit to promoting a culture of lifelong learning for all and building strong skills partnerships, with the Commission providing networking and knowledge hub services. Mike Cicco pointed to the Industry-Recognized Apprenticeship Programs (IRAP) in the US which provide individuals with opportunities to obtain workplace-relevant knowledge and progressively advancing skills. IRAPs include a paid-work component and an educational component and result in an industry-recognized credential. An IRAP is developed or delivered by entities such as trade and industry groups, corporations, non-profit organizations, educational institutions, unions, and joint labor-management organizations. Jeff Burnstein commented that ‘we have lots of good initiatives in the US, but the challenge is that they are not connected, or scaled’.
As we discuss in our ‘Next Generation Skills’ paper, manufacturing is the backbone of many economies and has an important role in generating jobs in related service industries. Even countries that have shrunk their manufacturing sectors in favor of service sectors need a strong core of expertise in manufacturing to drive growth. As Mike Cicco put it, ‘If you want a manufacturing sector in your country, you have to prepare for it, otherwise it will leave and may never come back.’
Automation is profoundly altering the face of manufacturing, creating promising new opportunities for employees at all skills levels. It’s an exciting future, for both new and existing workers, but a future whose potential will not be realized unless urgent action is taken to address an existing and future skills gap. This is the ‘challenge of the 2020s’ and one that requires close collaboration at scale to address.
Have you missed our executive roundtable? Then you can watch the recording at https://www.automatica-munich.com/en/newsroom/webinars/automatica-talk-nr-4/ or see the summary at the IFR YouTube Channel.
Picture © Universal Robots
Sales of service robots for professional and domestic use continue to boom, despite the economic downturn. In fact, economic uncertainty is one of the factors driving an increase in professional service robot sales, as logistics and manufacturing companies and hospitals turn to robots to smooth out the impact of unpredictable demand on labour requirements, and support staff in service sectors with labour shortages. Meanwhile, rapid technology advances are driving sales in high-value markets such as medical robots.
Logistics robots captured the largest share of unit sales, accounting for 43% of 2019 sales of professional service robots. Logistics robots are increasingly expanding their reach from service sectors into manufacturing. As we discuss in the recent paper, How Connected Robots are Transforming Manufacturing, autonomous guided vehicles (AGVs) are increasingly used to transport materials and parts to and from production lines while robots on mobile platforms can feed computer-numerically controlled (CNC) machines.
The category of mobile robots saw strong growth of 25% in unit sales in 2019 over the previous year. Like AGVs, mobile platforms can navigate around indoor spaces based on an internal map that is updated in real time, allowing the robot to ‘see’ obstacles and replan its path around them. Almost anything – from storage containers used in hospitals, to robot arms used to feed machines – can be placed on the mobile platform. Mobile robots have been used extensively in the current COVID-19 pandemic to deliver supplies in hospitals and support doctors in performing temperature and other checks. The versatility of mobile platforms makes this the strongest professional service robot growth sector. The IFR forecasts 97% average annual growth in unit sales in this category between 2020 and 2023.
Robots for public environments is the second fastest-growing professional service robot category in terms of unit sales, with a 44% increase in 2019 over 2018. These robots are typically used in hotels and restaurants, in public environments for guidance and information outlet, in stores or other public environments to promote sales or services, or as robot attractions such as joy rides. In hotels, robots carry suitcases to rooms, deliver room service, transport laundry, and greet guests. Information robots are used in a variety of public places, such as airports, to assist passengers in finding their gate number or shops to guide customers to the required product. Robots can also be used in restaurants to prepare and serve food and transport returned trays.
The COVID-19 pandemic has also driven sales in professional cleaning robots. Cleaning robots have been used to disinfect hospitals, public transport and supermarkets (see a variety of case studies here).The IFR forecasts that professional cleaning robots will be the second fastest-growing a professional robot sector in terms of unit sales - at 41% on average between 2020 and 2023.
Medical robots were the third fastest-growing category of robots (after robots for public environments and logistics robots) with a 33% increase in unit sales in 2019. Rehabilitation robots demonstrated particularly strong growth, with a 45% increase in unit sales. As we explore in recent case studies, the increasing sophistication of vision systems and data analytics means that robot-assisted rehabilitation generally produces better outcomes than purely manual rehabilitation, and frees rehabilitation professionals to focus on developing rehabilitation strategies and providing psychological support to patients. The IFR expects an annual average growth rate of 37% in unit sales of rehabilitation robots between 2020 and 2023.
Inspection robots was the fourth largest sector of professional robots in 2019 in terms of unit sales. Almost 15,000 inspection robots were sold, an increase of 32% over 2018. Growth in sales of inspection robots is largely driven by advances in robot vision and analytics technologies. Robots can be trained to recognise faults and sophisticated 3D vision systems result in a very high rate of accuracy in detection. The IFR forecasts steady growth in average annual unit sales of 27% between 2020 and 2023.
Sales of robots for personal and domestic use are dominated by robot vacuum and floor cleaners which accounted for 93% of unit sales of robots for domestic tasks in 2019. Going forward however, the category of robots for window cleaning, home security and surveillance and the category of robot companions, assistants, humanoids and multimedia are forecast to show strongest growth in unit sales, each with a forecasted average annual increase of 56% between 2020 and 2023.
The market for entertainment robots appears to be relatively mature, with only 10% annual average growth in unit sales forecast in this sector between 2020 and 2023.
Whereas production of industrial robots is dominated by Japanese manufacturers, the production of professional and domestic service robots is far more diverse. Of the 899 service robot companies captured in the IFR’s 2019 World Robotics Report – Service Robots, 49% are from Europe, 29% from North America, and 21% from Asia. American companies are strong in logistic systems whereas European manufacturers dominate in medical robots. Asian manufacturers are stronger in the category of field robots. The market is extremely vibrant – 23% of service robot manufacturers are start-ups.
Manufacturers across the world are confronted with multiple headwinds. First, ongoing demand for customized products which adds complexity to the entire production cycle. Second, labour shortages that leave many small-to-medium-sized manufacturers in particular unable to staff production peaks. Finally, geo-political uncertainty, particularly US-China trade conflict, and systemic shocks – most recently in the form of COVID-19.
As the 12% increase in the global operational robot stock (the total number of robots at work) recently reported by the International Federation of Robotics shows, manufacturers are turning to automation to remain competitive in this challenging environment. At the end of 2019, 2.7 million robots were at work around the globe, over three-quarters of them in manufacturing, predominantly in the automotive and electronics sectors. Detailed statistics on new sales and operational stock of robots across the world in different industry sectors and industrial applications are available in the IFR World Robotics Industrial Robots 2020 report.
As we discuss in a new information paper, ‘How Connected Robots are Transforming Manufacturing’, the rapid advances in automation technologies have expanded the range of tasks robots can perform. Robots are, increasingly, easier to install, program and re-task. Digitization means robots can transfer data to enable continuous performance optimization. Advances in communications protocols are making it easier to connect robots with other machines in the production process.
Though these advances have, in general, accelerated robot adoption, a challenging economic environment in 2019 for the manufacturing sector and the resulting tightening in capital investment led to a decrease in new robot sales for the year compared to 2018. The automotive and electronics sectors, which together account for 59% of robots in operation, were particularly under pressure. Global car and commercial vehicle production declined by 5.2% in 2019 over 2018. The automotive industry is re-structuring to address the demand for electric vehicles. The electronics sector, meanwhile, has been hit by the China-US trade conflict. These pressures were reflected in a decrease in new sales in both sectors in 2019. Nevertheless, the number of robots in operation in these sectors continues to increase, by an average of 10% annually between 2014 and 2019 in the automotive sector, and 19% on average annually in this period in the electronics sector.
China accounts for 32% of new sales of robots to the automotive industry and 51% of 2019 sales to the electrical/electronics sectors. Most of the robots sold to the automotive industry come from outside China. Chinese manufacturers focus heavily on domestic manufacturing sectors, of which there are over 100 in the country, many at very early stages of automation, such as textiles and consumer product manufacturing. The country is the number one robot market globally, accounting for 38% of new sales in 2019. China has also, since 2016, the largest operational stock of robots. Japan takes second place to China in terms of market share, but is the leading manufacturer of industrial robots, producing 47% of industrial robots sold in 2019.
Advances in robot technologies such as mobility, vision systems, grippers, connectivity and ease-of-programming are contributing to increased robot adoption in manufacturing sectors that have only recently turned to automation, such as food and beverage, textiles, wood products and plastics. The share of new robot sales in these sectors steadily increase, albeit slowly. Robot sales to the food and beverage industry have grown by 9% annually on average between 2014 to 2019 while sales of robots to the pharmaceutical and cosmetics industry increased annually by 14% on average during the same period. Both the technology advances mentioned above, and new business models such as packaged robot applications, and leasing of robots, will continue to drive adoption in these sectors in the future.
Overall, the number of robots per worker continues to increase. In 2019, the average robot density (the number of robots per 10,000 workers) in the manufacturing industry was 113, an increase of 12% over 2018. Robot density varies considerably by country, from 918 robots per 10,000 workers in Singapore to 1 in Egypt, Peru or Ukraine. Naturally, the extent to which a country’s economic output is driven by the manufacturing sector impacts the level of robot density.
Despite the increase in robot adoption, manufacturers still struggle to hire qualified workers, at all levels. In the US, for example, nearly 80% of manufacturers were struggling to fill over 400,000 open positions (according the US Department of Labor Job Openings and Labor Turnover – January 2020) and one third were forced to turn down new business in 2019 due to a skills shortage, according to the National Association of Manufacturers. As we discuss in our positioning paper, Demystifying Collaborative Robots, thanks to advances in collaborative robot applications, in which employees and robot work in the same space and in many cases are in direct contact, manufacturers are now able to address the skills shortage at least in part through robotic assistants and tools. Not only does this increase the productivity of existing workers, it also offers employees an opportunity to move away from tedious, unergonomic tasks to higher-skilled and better-paid work, for example programming and overseeing robots. The market for collaborative industrial robots in manufacturing is still in its infancy, accounting for only 4.8% of the 373,000 industrial robots installed in 2019. However, sales of collaborative industrial robots increased by 11% in a difficult year which saw overall new installations decline by 12% globally. Statistics collected by the IFR on collaborative industrial robots refer to robots that are designed specially to work in collaboration with humans (also termed cobots). In addition, a large number of manufacturers are using other external technologies such as sensors and robot skins, to enable collaborative robot applications. It is not possible to capture these applications in the IFR statistics, but reports - and case studies – from IFR members give a strong indication of the promise of collaborative robotic applications, achieved through either cobots or adaptations of the robotic cell.
The COVID-19 virus has made it very difficult to make accurate predictions and this applies to forecasts of robot adoption. On the one hand, robots have come to the fore in the COVID crisis, giving manufacturers increased flexibility and enabling safe working conditions in both manufacturing and non-manufacturing environments. On the other, low economic growth resulting from COVID 19 will inevitably impact capital investments going forward. The IFR has modelled three main recovery scenarios in the World Robotics Industrial Robots 2020 report. Though varying in the annual trajectory of robot sales, all see an initial downturn in robot sales. Recovery will not take place simultaneously around the globe. While there are already promising signals from China, Europe is still at the bottom of the valley. Overall, recovery is expected for 2021 but it is unlikely that pre-crisis levels will be achieved before 2022 or 2023, depending on the further development of the COVID pandemic and its economic impact.
Robots have historically not been widely used in machining applications, but that may be about to change. We look at the benefits of robots in machining, and how researchers are overcoming some of the traditional constraints of using robots for machining applications.
Machining functions such as cutting, welding, grinding, deburring, milling and polishing have historically represented a relatively low percentage of robotic applications. In 2018, for example, welding and soldering, dispensing and processing (cutting, grinding, de-burring, milling and polishing) accounted for only 25% of total applications of industrial robots.
This may be about to change, for a number of reasons. First, robots are increasingly price-competitive with traditional machine tools. Second, robots offer benefits over machine tools for certain machining applications, particularly those requiring broad reach such as the deburring or polishing of large parts for aircraft or wind turbines. Polishing of large surfaces is often carried out manually, potentially costing manufacturers substantial sums due to muscle strain in production workers. Robots are a viable alternative for these applications as they can be mounted on mobile platforms for extended cover and are considerably less expensive than machine tools for applications requiring high reach.
Third, the very high levels of precision afforded by machine tools are not needed in some sectors and applications. For example, in furniture manufacture or plastics, and in applications such as milling and drilling, a level of precision up to the millimetre is sufficient (versus precision to the micrometre afforded by machine tools). The rigidity of a machine tool is vital in applications such as cutting that require very fine precision. However, in applications such as polishing, greater compliance (i.e. lower rigidity) offered by robots is an advantage as it avoids scratches in slightly uneven surfaces. (e.g. see video boat sanding with mobile robots)
Many pre-production processes – for example removing rust from large metal sheets before cutting – lend themselves well to robotic applications. Many of these tasks are currently carried out manually and would be too expensive to automate through a machine tool. A robot application can come in at around half the cost of a machine tool for many applications that were previously carried out manually.
Finally, robots are easy to programme for a wide range of applications - in many cases simply by guiding the robot arm through the motion to be carried out. Robots can also be quickly re-programmed and applied to new tasks. This gives manufacturers a high level of flexibility which is critical in dealing with short production runs and peak periods. For small-to-medium-sized manufacturers in particular, this flexibility is critical and offers a higher return on capital than an investment in a machine tool that is limited in application. Robots can also be programmed through a machine tool computer-numerically controlled (CNC) controller, which means that code generated by computer-aided-manufacturing (CAM) systems for machine tools can also be used by robots.
Given the flexibility of robots for multiple tasks in the manufacturing process, researchers have been looking into overcoming some of the traditional constraints associated with using industrial robots for machining applications. For example, BAE Systems estimates it will save millions of dollars in capital and operational costs by using robots to accurately machine holes in composite aircraft components. The application, which developed out of a research project led by the Advanced Manufacturing Research Centre (AMRC) at the University of Sheffield, UK, and involving KUKA Systems UK, uses multiple robots to automatically handle composite components and then countersink high tolerance pre-drilled fastener holes. Non-contact metrology integrated with the machining robot locates predrilled holes and corrects the robot’s position before countersinking. A separate robot provides support to the component eliminating expensive holding fixtures. See the full case study here.
A paper co-authored by Professor Alexander Verl, Chair of the IFR Research Committee1, summarises further research into improving the applicability of robots for machining applications. For example, several advances have been made that improve the use of robots in deburring applications. These include offline programming, which enables manufacturers to simulate the application in advance and automatically generate a robot programme for the optimal application. Vision technologies can also be used to generate images for programming and may be helpful in determining the exact position and dimension of burrs.
Researchers have been able to model adjustments in robot position and cutting parameters in milling applications to reduce the impact of external forces that lead to vibrations. These adjustments increase the stiffness of the robot joints and, as a result, the stability of the machining operation.
Researchers led by Dr Erdem Ozturk, from AMRC at the University of Sheffield have also found benefits in using robots in combination with machine tools, opening the potential for new applications. For example, robots can be used to assist in the machining of thin wall parts where high form errors and vibration are common. Researchers found that using a robot equipped with a mobile rubber roller to support the feed motion of the machine tool enabled significant improvement in reducing form errors and improved surface quality due to decreased vibration.
This video shows the benefit of using a robot to stabilize an aluminium part that is being machined.
Hybrid-manufacturing processes, using robots to preform two or more processes within the application, have also been successfully tested. For example, different cladding techniques such as friction surfacing can be combined with a robotic milling process to produce nearly-finished components for further processing. Other process combinations include drilling, reaming, assembly and quality assurance within one robot cell, enabling the part to remain clamped in one position while the robot performs all four tasks.
The European Union’s Innovation Radar project has gathered a number of applications of robots in machining that show commercial potential. These include the use of robots for smart weld grinding and finishing, mould sanding, metal part grinding and robotic mobile fixture. Many of these were developed through the EU-funded COROMA project coordinated by Ideko, Spain which focused on the development of a cognitively enhanced robot that can execute multiple tasks for the manufacturing of metal and composite parts. A video showing robots in action in some of these applications can be found here.
Robots will not be replacing machine tools any time soon for a wide range of machining applications that require high precision afforded in part by the ‘stiffness’ of machine tools. However, given the greater flexibility of robots across a wide range of tasks, including machining, manufacturers should assess their overall production requirements and determine where the use of robots makes most sense. This can include machining applications with requirements for precision within the millimetre rather than micrometre range, high reach and applications for which a level of yielding to resistance is beneficial. Manufacturers currently conducting production tasks such as de-burring and ‘roughing’ (initial part cutting) manually should consider robot adoption as a flexible, cost-effective alternative, enabling workers to move to more satisfying tasks supervising and re-programming robots.
Co-Author: Dr Erdem Ozturk, AMRC at the University of Sheffield, UK
1Robots in Machining, Verl et. al. CIRP Annals – Manufacturing Technology 68 (2019)
Teaser picture: Robot-machining of laser-cladded paths © Abele 2017 Form Werkzeug Carl Hanser Verlag
‘World Robotics R&D Programs’, compiled under the leadership of Professor Jong-Oh Park of Chonnam University, provides a valuable resource for researchers, investors and policy makers looking to understand different countries’ strategies for developing their respective robotics sectors.
Information was gathered from 20 countries and regions. As many of these countries do not run specific government-led research programs into robotics, or could not provide robust data, the final report focuses on eight countries or regions – China, Japan, Korea, Germany, USA Sweden, Italy and the EU. The report makes accessible - in English - material from key Asian and European countries that is otherwise only available in the local language.
The analysis shows substantial variance in government investment in robotics, with the Chinese government – the largest investor in robotics research by total dollar amount– spending USD 577 million in 2019 on robotics research, compared with an investment of USD 35 million dollars in the US, through the National Robotics Initiative. China has been the world’s largest industrial robot market since 2013 and accounted for 36% of total installations in 2017 and 2018.
Japan, which in 2018 provided 52% of global supply of industrial robots according to the IFR, is the second largest public-sector investor, with USD 351 million assigned to robotics research in 2019. Korea, which has the second-highest number of robots in operation per manufacturing employee, has a robot-related budget of USD 126 million for 2020.
The report, which can be downloaded here, provides a valuable comparison of the different areas in which each country seeks to establish a competitive advantage through funded research in robotics.
China has set out very concrete and ambitious goals for its robotics sector. In the 2013 ‘Guideline on Promoting the Development of the Industrial Robot Industry’, the government aimed by 2020 to: Develop three to five globally competitive robot manufacturers; Create eight to ten industrial clusters; Achieve 45% of domestic market share for China’s high-end robots, and; Increase China’s robot density to 100 robots per 10,000 workers. The IFR report World Robotics 2019: Industrial Robots shows that China reached a robot density of 140 units per 10,000 workers in the manufacturing industry in 2018. In 2016, the Robot Industry Development Plan (2016-2020) was announced with the aims of expanding the scale of China’s robotics sector, strengthening technological innovation capacity, improving core parts production capacity, and improving application integration capacity. Ten robotic solution areas, such as welding, cleaning and human-machine collaboration and 5 component technologies including sensors and high-performance controllers have been prioritized. China has a very diverse manufacturing industry, with over 100 different sectors including leather and fur manufacturing, wood processing, machinery and equipment repair, pipeline transportation and furniture manufacturing. Many of these sectors have only just begun to automate and Chinese robot manufacturers collaborate with potential customers – many of them small-to-medium-sized businesses – to develop new applications.
All of the main robot-producing countries have placed a focus on the development of robotic applications for healthcare. Robots are already used extensively in hospitals for a variety of tasks; fetching and carrying medications and linens, acting as ‘virtual assistants’ through telepresence applications, increasing the efficiency of medical testing, disinfecting hospital rooms and supporting patients in rehabilitation of limbs after injury and illness. As aging populations place an increasing burden on healthcare systems, we can expect to see robots playing an increasingly extensive role assisting doctors and nurses in patient care and safety.
Both Japan and Korea have identified agriculture and disaster response as target industry sectors for the development of robots and robotic applications. Field robots accounted for over 11 percent of sales of professional service robots tracked by the IFR in 2018 (see World Robotics 2019 - Service Robots). This is a rapidly growing sector which the IFR expects to expand by 45% on average year-on-year between 2019 and 2022.
As part of the cross-ministerial Strategic Innovation Promotion Program (SIP), the Japanese government has also prioritized manufacturing, service sectors and infrastructure and construction for the development of robot applications. The Korean government’s ‘3rd Basic Plan for Intelligent Robots’, which runs from 2019 to 2023, focuses, in addition to agriculture, healthcare and disaster response mentioned earlier, on service robotics, wearable devices, logistics, underwater exploration and defense.
In the US, government funding for robotics is provided by The National Robotics Initiative (NRI) which, with a budget of USD 35 million, focuses on technologies and systems to achieve a vision of ubiquitous collaborative robots assisting humans in every aspect of life. Additional robotics funding for applications in defense and space is provided through the Department of Defense (DoD) and the Mars Exploration Program.
Robotics funding by the EU has been directed through the current seven-year research framework program Horizon 2020, which runs from 2014 to 2020 and covers a wide range of research and innovation topics including manufacturing, consumer, healthcare, transportation, and agri-food robotics. The final work program runs for three years from 2018 to 2020 with a budget of USD 172 million. It focuses on digitization of industry through robotics, robotics applications in promising new areas, and robotics core technologies such as AI and cognition, cognitive mechatronics, socially cooperative human-robot interaction, and model-based design and configuration tools. The next seven-year research framework program, Horizon Europe, starting in 2021, is currently in development and will reflect recent efforts to boost global R&D to address the corona pandemic.
The German government has placed a strong focus on leadership in ‘Industry 4.0’, focusing on the adoption of advanced automation technologies in manufacturing, and the digitization of business models in other sectors. The ‘Industry 4.0’ initiative, which falls under the overall High-Tech Strategy launched in 2006, covers various aspects of robotics through 5-year programs. The current PAiCE program (Platforms | Additive Manufacturing | Imaging | Communication | Engineering), launched in 2016 with USD 55 million dollars in funding, focuses on the development of digital platforms and the collaboration between companies using them. Robotics-oriented projects focus on the creation of platforms for service robotic solutions in service sectors, logistics and manufacturing.
We are grateful to the IFR Research Committee, and particularly to Professor Park and his team at Chonnam University, for compiling the World Robotics R&D Programs’ report. This is a unique and valuable resource that gives organizations a concise overview of different governments’ priorities in robotics development to help guide investment and partnership strategy.
Historically, robots have been standalone machines, each with their own vendor-specific programs. When robots ‘talk’ to other machines – generally through an external controller - the communications interface must be programmed specifically for each type of machine. Code developed for one make of robot controller cannot generally be transferred to another, even if the task being carried out – for example, instructing the robot to run at a specific speed - is exactly the same.
Manufacturers today are increasingly implementing automation strategies to increase productivity, cut costs through just-in-time manufacturing and respond to the demand for smaller, customised production runs. As a result, more and more machines are connected, and produce data which can be stored and analysed to improve production performance. This has led to a significant increase in the complexity and overhead of programming. Many manufacturers struggle to gain an overview of the status of all the machines on the production floor along one common parameter (for example speed and position of robot axes) since each vendor specifies these parameters differently.
To address this issue, the mechanical engineering industry association in Germany and Europe (VDMA) teamed up with the OPC (Open Platform Communications) Foundation to create a common interface for all types and components of robot systems* such as industrial robots, mobile robots, control units and peripheral devices. The joint initiative aims to establish standard interfaces to enable the extraction and exchange of information from different robot manufacturers in a standardised way, irrespective of the manufacturer.
The OPC Robotics Companion Specification is a communications technology model which allows manufacturers to associate different terms or blocks of code with one common semantic definition. For example, the term ‘serial number’ surfaces data on the robot’s serial number, irrespective of how this is specified in the proprietary robot program.
The OPC Robotics Companion Specification is being developed in stages by a working group of around 35 companies comprising robotics suppliers, control manufacturers, integrators and automotive companies that use robots. Part 1 – covering asset management and condition monitoring – was released in September 2019. It enables organisations to surface information on the operational status of their robot systems, down to the individual component level. Companies can monitor the condition of their robot systems against given parameters – for example motor temperature, load or time cycle. This information can then be integrated into applications pertaining to use cases such as predictive maintenance, in which machine performance data is analysed to detect if a specific part is likely to need maintenance. Manufacturers can then plan maintenance before the situation becomes critical and the machine malfunctions, potentially causing expensive production downtime. The specification provides detailed information about the main electrical and mechanical parts such as part number, brand name and serial number. Technicians can therefore see exactly which part needs to be changed if a machine is not adhering to given thresholds, rather than discovering this only during the maintenance process.
Part 1 covers ‘vertical integration’ – referring to the robot and any technology that controls it, such as a Manufacturing Execution System (MES) or Programmable Logic Controller (PLC). Subsequent parts of the Robotic Companion Specification will cover geometrical descriptions of a robotic system (tracking the movement of the robot in a 3D space) and various aspects of controlling the robotic system, for example up /downloading and starting /stopping programs, confirming system messages and switching drives on and off. Having a standard semantic reference for each of these tasks enables manufacturers to easily gain a real-time view of production. For example an automotive manufacturer tracking an order for 10 cars of Type A and 5 of Type B can see exactly what stage of completion the order has reached for car type A by tracking downloads for the various programs needed to produce car type A. These programs will typically be distributed across multiple robot systems that are also working on car type B.
Other OPC Universal Architecture Companion Specification groups within VDMA are developing models to enable similar vendor-independent specification for other machines such as injection moulding machines and machine vision systems. Once available, these will enable horizontal integration between robots and other machines in an automation process.
To find out more about the OPC Robotics Companion Specification, see the following videos:
Further information is also on the VDMA Website here
* OPC robotics covers a motion device system that includes any existing or future robot type, control systems and software
UK manufacturing faces multiple challenges. The most significant is a long-running fall in productivity compared to the manufacturing sectors of other OECD countries. A report the UK’s Cranfield University found that, compared to the United States, China, Germany, Japan, India, Poland and France over a 10-year period from 2006 to 2016, the UK was the only country where productivity per person per hour actually decreased (by 9%). All the other countries mentioned saw an increase, with Germany, for example, raising its productivity rate by 21%1. The UK’s manufacturing sector has fared little better since the report was published, with a 1.9% decrease in output per hour in the sector in the third quarter of 2019 compared with the same quarter in the previous year.
Uncertainty over Brexit has already taken its toll. Sixty-four percent of manufacturers say Brexit delay has already had a negative impact on their company’s profit margin over the last two years, with 76% concerned that a no-deal Brexit will have a negative impact on the willingness of EU customers and suppliers to do business with them2. Twenty-five percent of companies surveyed by the Bank of England reported having reduced capital investments due to Brexit3.
More recently, the coronavirus is putting a strain on global productivity. The OECD has halved its growth forecast for 2020 to 1.5% over 2019 if the virus continues escalate. Manufacturing sectors are experiencing significant supply chain disruption which has yet to be quantified.
Yet even in the face of economic uncertainty, UK manufacturing’s low productivity is not a given. There are two obvious and actionable solutions to the current productivity crisis:
UK manufacturers must provide workers with the tools - including robots – to do their jobs more effectively. There is a clear link between robot adoption and productivity increases. For example, a study by Centre for Economics and Business Research found that investment in robots contributed 10% of growth in GDP per capita in OECD countries between 1993 and 20164 while the OECD found that companies that employ technology innovations effectively are between 2 and 10 times more productive than those that do not5.
There is also an established link between robot adoption in manufacturing and growth in jobs and wages. This may seem counterintuitive since the robot initially replaces a worker in specific tasks. However, there is clear evidence that the increased productivity driven by robots leads to greater competitiveness and therefore higher demand, as well as quality improvements and the ability to manufacture customised items competitively. Moreover, workers in robot-intensive manufacturing companies are better paid. For example, a study by PwC found that in the US, the most robotics-intensive manufacturing sectors employ about 20% more mechanical and industrial engineers and nearly twice the number of installation maintenance and repair workers than do less robotics-intensive manufacturing sectors and pay higher wages than other manufacturing sectors. These sectors also tend to have a higher proportion of production-line workers — and these workers earn higher wages than sectors that are less robotics-intensive6. Other studies confirm that robots have increased wages without reducing hours worked7 and that jobs have grown faster in occupations using automation8. This matters because the UK’s manufacturing sector currently employs just under 3 million workers, with many more jobs in support and service sectors dependent on a thriving manufacturing industry. The manufacturing sector is more important to the UK economy than many people think. For example, it forms a larger part of the UK economy than either financial service or construction, contributing over 10% of economic output.
It’s therefore vital that the UK’s manufacturing sector turns to automation – and robot adoption - to boost productivity and competitiveness. Yet the UK lags significantly behind manufacturing competitors. According to the industry association International Federation of Robotics robot density (the number of robots per 10,000 workers) in the UK’s manufacturing industry was only 91, compared to German and Japan with over 300 robots per 10,000 workers and Singapore with 831. Low robot adoption is compounded by a skills shortage in the qualifications needed to drive automation. The British Chambers of Commerce (BCC) found that 81% of manufacturers reported difficulties with finding staff with the right qualifications and experience in 20189, while the Confederation of British Industries reported in its most recent quarterly manufacturing report that one third of firms surveyed cited labour shortages as a factor likely to limit investment - the highest number on record10.
Robots have, for decades, performed the heavy lifting in automotive and other manufacturing sectors, carrying out dangerous and monotonous tasks at high levels of precision and speed and ensuring the productivity and competitiveness of vital manufacturing sectors. Over the last decade, robots have come out of their cages and are used as tools and, increasingly, as intelligent assistants to manufacturing operators and technicians. Robots perform a rapidly increasing range of tasks, can be programmed and moved from one task to another in a matter of hours with minimum operator training, and are increasingly financially viable for manufacturing sectors that have been slow to automate. This is particularly important for the UK’s food and beverage sector, which accounts for 20% of the UK’s manufacturing output and provides 400,000 jobs in addition to supporting jobs in agriculture, packaging and logistics. Brexit increases the imperative for food manufacturers to automate, since this sector employs a high number of non-UK workers. Many of these workers are returning home due to Brexit uncertainty and their numbers will be further restricted if a planned policy restricting low-skilled EU immigrants to the UK post-Brexit comes into force.
BARA has recognised the opportunity for UK food manufacturers to increase productivity and competitiveness through robot adoption and has a number of initiatives in place to help food manufacturers develop automation strategies and find appropriate automation suppliers and systems integrators.
The UK ranked only 8th in a recent Automation Readiness Index conducted by the Economist Intelligence Unit11, lagging behind manufacturing competitors such as Germany, Japan and South Korea in key areas such as the overall innovation environment, investment in R&D and skills and labour market policies. The UK also trails behind many of these countries in the World Economic Forum’s Global Competitiveness Index. Boosting the enabling environment for manufacturing, particularly in regions in the North of England that have struggled to recover from recession, must be a priority for the UK government. In particular, the government must ensure that the deal it negotiates for its future relationship with the EU does not disadvantage UK manufacturers.
Brexit and the coronavirus place the UK’s manufacturing industry in a time of great uncertainty. The usual response would be to hold off capital investment until there are visible signs of improvement. For UK manufacturers, this would be a mistake. Delaying investment in automation risks compounding the long-running issue of falling productivity in the sector which won’t go away once the UK has agreed a trade deal, and the coronavirus has passed. I urge UK manufacturers to take a longer-term view and invest now in robots and associated automation processes and tools vital to growth and competitiveness.
Picture: © Kuka
1 Industrial Strategy and UK Manufacturing - A white paper by Cranfield University, 23 May 2018
2 Preparing for Brexit: Deal Or No Deal - Make UK and Squire Patton Boggs, October 2019
3 Staff Working Paper No. 818 The impact of Brexit on UK firms - Bank of England, August 2019
4 The Impact of Automation, Centre for Economics and Business Research, 2017
5 The Future of Productivity - OECD, 2015
6 The New Hire How a New Generation of Robots is Transforming Manufacturing – PwC, 2014
7 Study by Georg Graetz and Guy Michaels - Centre for Economic Performance at the London School of Economics
8 Robots Seem to Be Improving Productivity, Not Costing Jobs - Harvard Business Review, 2015
9 https://www.britishchambers.org.uk/news/2019/01/bcc-quarterly-economic-survey-big-squeeze-on-firms-from-recruitment-prices-and-cash-flow accessed 14.03.20
10 https://www.cbi.org.uk/media-centre/articles/uk-manufacturing-business-optimism-improves-at-the-strongest-pace-since-2014-cbi/ accessed 14.03.20
11 Automation Readiness Index - Economist Intelligence Unit, 2019
Robots are playing an important role in combatting the coronavirus. We look at some of the ways in which robots are keeping people safe, fed, and able to access the care they need through the pandemic.
With many countries in full or partial lockdown to halt the progression of the coronavirus, robots are stepping in to perform vital tasks that keep people safe and enable virtual contact. Many robot suppliers are donating or lending robots to hospitals and care homes to help stem the spread of the virus.
Here are some of the ways robots are being put to work:
Robots are used in hospitals to disinfect rooms using ultraviolet rays that also kill the coronavirus. Ultra-violet disinfection robots can destroy 99.99% of all microorganisms in a hospital room within 10 minutes. While the room must be empty during disinfection, there are no negative effects of the UV rays. The robot’s route can be planned by hospital staff through an app and, once activated, cleaning robots move autonomously from room to room. On arrival, the robot makes an announcement asking anyone in the room to leave and close the door at which point cleaning can begin. Many of these robots can also operate lifts.
Many hospitals already use these robots to combat infections caught during hospital stays, which account for around 37,000 deaths per year in Europe and almost 100,000 in the U.S. However, suppliers of cleaning robots have experienced a surge in demand due to the spread of the coronavirus.
In Hong Kong, cleaning robots are now being used to clean carriages in the city’s Mass Transit Railway, which transports millions of passengers every day. The newly designed robot supplements the work of cleaning staff by spraying a hydrogen peroxide solution on to surfaces, focusing particularly on small gaps that human hands cannot reach.
Robots are being used to treat patients with the coronavirus, enabling doctors and nurses to carry out tests and interact with patients at arms length. The first US patient diagnosed with the virus was treated by a remotely-controlled robot equipped with a stethoscope and a screen that enabled doctors and nurses to communicate with the patient and take simple measurements.
Robots, from suppliers such as KUKA and Universal Robots, are used extensively to automate the lab work, e.g. the processing of samples, vastly improving the productivity of testing for bacterial and viral infections. Also Yaskawa and ABB are collaborating with hospital and medical labs to develop applications where their two-armed robot support the staff and speeding up testing.
Now, a robot that automates the process of taking mouth swabs, in order to test for the virus, is in clinical trials in China. The aim is to reduce infection risk to medical staff by eliminating the need for contact. Developed by Shenyang Institute of Automation, Chinese Academy of Sciences, the robot can sense contact and pressure and is able to gently take a sample that is then sent for analysis, with no human interaction required.
Many countries are advising or mandating that older people stay at home and refrain from contact with any family members not already living with them. This creates a dilemma for carers in residential homes for older people. Telepresence robots, already used in many assisted-living homes to enable older people to live independently for longer, are stepping in to keep elderly people in touch with carers and family. The image of the remote user is displayed on the robot’s screen and the robot can be directed around the room to view anything in its vicinity. Most of these robots are controllable from any location with a smartphone or computer and internet connection. Family members, friends, doctors, and care givers can all log into the telepresence robot, drive it, interact with others, and explore the environment with audio and video.
Robots are used in a wide variety of sectors for delivering parts, supplies and food. Delivery robots – such as those from IFR members MIR and Photoneo - are already used extensively in hospitals to deliver medical supplies and heavy items such as bedding throughout hospitals, saving nurses and orderlies many hours of time. Typically, these robots deliver items to nurse stations, but they are now being used to make deliveries directly to patients in isolation both in hospitals, and in other locations. For example, robots delivered food to people who had been on a flight with passengers infected with the virus and subsequently ordered into quarantine in a hotel in Hangzhou, China. The robot announces its arrival at the door and the occupant takes their food tray off the robot’s inbuilt shelf.
Delivery robots are also being used to bring groceries and pre-prepared meals to people, and to dispense hand sanitizer in public places.
Robots are starting to be used in food preparation, making pizza and in-store bread, for example. Now they have been enlisted in the effort to stem the spread of the coronavirus. Robots have been used in China to prepare and serve food to medical workers so that hospital canteens do not need to be staffed round the clock. A food preparation robot delivered to a hospital in Wuhan, China, reportedly prepared 36 portions of rice casserole every 15 minutes.
Mobile information robots are increasingly used in public spaces, for example airports and trade fairs, and in shops, to help people get to their destination and find goods more easily. Information robots are also playing their part in keeping people safe by keeping them informed and reminded of safety precautions related to the virus. A robot, supplied by Russian manufacturer Promobot, was recently rolled out in various locations in New York City to converse with passersby, who could also fill out an online questionnaire on the robot’s touchscreen. The robot can also be equipped with a thermo reader to detect early symptoms of covid-19 like elevated temperature.
Meanwhile in China, UBTECH robots have been used at a hospital in Shenzhen for temperature monitoring of patients and visitors outside and inside the hospital and distribution of hand sanitizer, as well as providing information about the virus to arriving visitors.
In the current situation, we also well benefit from robots as flexible manufacturing tools that can quickly be reprogrammed to service changing needs.
Robots are for example being drafted in to speed up the production of medical equipment such as surgical masks that are in short supply. Chinese robot manufacturer SIASUN has set up over 100 robotic production lines for face masks, for example.
Also assembly equipment manufacturer PIA Automation helps to respond to the sharp increase in demand for face masks and other personal protective equipment (PPE). The assembly equipment manufacturer offers fully automated assembly lines for the high-speed production of protective masks. Orders for 21 of these mask production lines have already been received. Each line can produce 140,000 pieces per day and even cover several product variants of two-, three- or four-layer disposable masks. The manufacturing process includes feeding of filter material, folding and pressing, feeding of nose bridge clips, forming of the masks, cutting of the masks, welding of the ear straps, packaging and other auxiliary processes. In order to meet the increased global demand, the machines are built in plants in China, Germany and the USA, which are distributed all over the world.
Small-to-medium sized companies in a range of industries - from manufacturing to logistics, food processing, retail and healthcare – are investing in collaborative industrial robots that can support workers by completing fetching-and-carrying, heavy lifting, machine feeding, shelf-filling and other monotonous tasks. Employees are able to focus on higher-value tasks, from spending time with patients and interacting with customers, to overseeing multiple small-batch production runs. These robots are particularly useful for companies with variable demand for human resources, either because demand is seasonal, such as in retail and agriculture, or because orders are unpredictable as can be the case in manufacturing. These robots are ideal in times of short-term labour shortages, such as the current coronavirus, as they can be easily programmed to take over tasks of missing employees, and then shift back to other duties once those employees return to work.
Robots used in a Chinese hospital for disinfection, delivery, and monitoring the temperature of arrivals. Source: South China Morning Post
Telepresence robots enable carers and family to keep in touch with elderly people Source: Telepresence Robots
A robot delivers food in a Chinese hospital. Source: New China News
Delivery robots bring food and pre-prepared meals, and dispense hand-sanitizer. Source: CGTN
The robot chef at a Wuhan hospital. Source: The Paper
We see plenty of opportunity in our existing markets, particularly logistics. Today there are only around 15 service robot companies targeting the logistics market, but even if there were 100, there would still be a huge market opportunity. Remember that traditional industrial robot companies have had 50 years of market growth in manufacturing, with no real pressure to diversify to other sectors. We’re now seeing collaboration with industrial robot manufacturers in newer sectors like logistics, where they supply the robot arm, and service robot manufacturers provide mobility and workflow planning.
The other market where I see a big opportunity for service robot manufacturers is in elder care. There are so many potential opportunities for using service robots to assist overburdened healthcare workers in fetching, carrying and load bearing. But there are technical hurdles that we need to address. In particular, we need sophisticated sense-and-respond technologies when dealing with fragile patients. For example, if a patient leans on a robot for support, the robot needs to be able to sense that pressure and not start to move until it has gone.
In Asia, we see companies focusing on applications for direct robot-patient interaction. I think there is greater cultural resistance to that in the US and Europe so in these markets we’ll see more service robots being used to support caregivers rather than interacting directly with patients.
There are two areas of development that are especially important. One has to do with enabling humans and robots to work together in increasingly close interaction and collaboration. The other is business models that enable more companies to adopt robots, and robot providers to offer additional value-added services to their customers.
Many customers want a very fast-moving robot that might be working with heavy weights, that is still collaborative. Those capabilities have historically not been compatible – as soon as you have a very fast-moving robot, or one working at speed with heavy parts, it has been caged. That’s starting to change and will continue to do so, thanks to improvements in sense-and-respond technologies. The sensor market is moving at a rapid pace – I saw at least 15 new laser companies at last year’s Consumer Electronics Show, for example. Manufacturers of robot arms are increasingly building sense-and-respond capabilities – power-force limiting, torque-sensing – into the robot arm and developers are working on tactile capabilities for grippers and other end effectors.
We’re going to see more complex applications that combine data from multiple sensors in real time – from 2 or more robots, plus external sensors in the warehouse or factory, for example – and use sophisticated algorithms to enable the robot to respond accurately to their environment. We’re gradually stretching the envelope from robots traditionally only working in very structured, predictable environments, to robots working in semi-structured environments with workers, for example in manufacturing cells. Having robots work directly with humans in very unstructured environments – for example in construction, helping a worker lay tiles in an irregular pattern – is further off. The technologies for manipulation and dexterity are there, the issue is how to get the robot to do the right thing at exactly the right time.
The second area I think is very promising, and which we’re investing heavily in at Fetch, is Robots as a Service (RaaS), where customers rent a robot rather than owning it. This frees up valuable capital. It also means the company doesn’t have to hire technicians to maintain a fleet of robots from a number of different manufacturers with different technical requirements. The RaaS model is timely because many large companies currently have ageing equipment, including robots, that they are thinking about replacing. For smaller companies, RaaS offers an easy entry into robotics, with low training and maintenance costs, and no sunk capital.
I would predict that over the next 5 to 10 years, we’ll see up to 70% of professional service robots in the market being acquired by customers in a RaaS model, particularly among small-to-medium sized companies. We’re seeing the RaaS model take hold in the industrial robot market too, but I think development there will be slower as the ownership model is more heavily ingrained with large manufacturers.
The combination of these two trends – more sophisticated sense-and-respond capabilities and a cloud-based robot service model – enables service robot manufacturers to provide services that add value beyond the return on the robot doing the job it was hired for. I see three areas for added-value services. The first is in productivity improvement – analysing robot data and data from other sensors to analyse and improve workflows. The second is in safety. For example, we can perform near-miss analysis that takes data from multiple sensors and analyses it to see where a collision was only narrowly avoided or avoided at the cost of machines having to slow down. The third area is in auditing and compliance. Service robots are already used in retail to audit stocks and ensure shelves are filled. But there’s also an opportunity for auditing customer moods. Many service robots in retail interact visually with consumers through video or photos. Imagine the opportunities for improving store layout and service if that data could be analysed to analyse a customer’s mood as they move through the store – what delights them, what annoys them. Finally, the data collected through sensors can also be used to ensure compliance – for example, that fire-extinguishers are in the right place and fire doors are not blocked.
Customers are mostly concerned about cyber-security in a cloud-based model, but the large cloud storage vendors have by now gained significant experience and use sophisticated cyber-security tools. Actually, the highest security risk is on the customer side is in managing passwords safely, for example though 2-factor authentication.
For the robot service provider, the biggest challenge is getting the data off the robot as more and more sensors are added. At Fetch, we’re investing in algorithms and compression techniques to deal with that. Currently, robot providers work with the data extracted from the robot to provide services to customers. I think we’ll see the rise of robot infrastructure companies that offer robot fleet management and data management, who will also provide data analytics toolkits to customers to do some of the work in areas like productivity improvement and workflow analysis themselves.
I’m hoping to focus on providing members with reliable information on trends and markets that will enable them to make good investment and business-strategy decisions. Service robotics is a very broad field and it’s difficult to collect market data covering all manufacturers and application areas. I think the IFR has the competence and reputation to offer reliable, up-to-date market information to members which means we can engage more service robot providers in providing the data needed to make these statistics comprehensive across the service robot sector.
Picture: © Fetch Robotics
Training programmes and other incentives are vital to enable the workforce to successfully adjust to the impact of automation. We look at some of the initiatives underway in different countries to adapt and profit from the growth in automation, including robot adoption.
The IFR Positioning Paper ‘The Impact of Robots on Productivity, Employment and Jobs’ provides evidence from range of studies by leading economists that automation has led overall to an increase in labour demand and positive impact on wages. History shows us that automation leads to a shift in the type of labour in demand. In most cases, the shift results in changes to existing roles and a requirement to acquire new skills. Less often, existing roles become redundant and workers must apply new and existing skills in new sectors.
Governments and private-sector organisations have recognised that the speed and scale of technological change call for additional investments in providing the right skills to current and future workers to ensure a continuation of the positive impact of automation on employment, job quality and wages. In this blog, we provide an overview of the major types initiatives underway to prepare the workforce for automation. We will continue to report on specific initiatives from individual countries in future blogs.
A rapidly changing technology landscape and a labour market in which employees either want to, or must, acquire new skills on an on-going basis to maintain relevance call for new approaches to skills acquisition.
The number of students enrolled in higher education institutes has doubled globally since 2000, reflecting demand by employers for higher qualifications and a desire by students to enter higher-income professions. However, there are signs that this trend has contributed to disparity in skills supply and demand. This has left many companies short of adequately skilled staff to profit effectively from automation, and students short of the qualifications that lead to employment security in mid- to high-income jobs. As we discuss in detail in our positioning paper ‘Robots and the Workplace of the Future’, the production and logistics sectors are struggling to hire qualified staff. And while digital skills are deemed a pre-requisite by employers across all sectors, most employers place increasing emphasis on ‘soft’ skills such as communications, teamwork, situation analysis and decision-making.
Governments, education institutes and private-sector organisations have recognised this and are working on initiatives to better match skills and qualifications to market demand, as well as incentives and programmes for life-long learning.
Germany has a long tradition of matching skills training to demand, both through higher education, and through apprentice trainee schemes that do not require a higher education qualification. The ‘Duales Studium’ (parallel study) system enables students to complete a higher education qualification while working for a company. Seventy-five percent of Duales Studium students are employed on full (non-fixed-term) contracts following their studies, versus 50% of students in other higher education programmes. Switzerland uses a similar model. South Korea – where a greater percentage of young people complete higher education than any other OECD country – has introduced a ‘Meister’ vocational training programme aimed at addressing a skills demand gap which, according to the World Economic Forum, led to 42% of Koreans being overqualified for their jobs in 2014. A number of Italian universities offer master’s degrees in applied automation. Curricula are generally developed in close collaboration with private sector companies and research establishments to ensure students are trained in cutting-edge technologies and giving the private-sector companies involved access to highly-skilled workers.
Governments in a number of countries have developed programmes and incentives to ensure that employees can continuously update their skills to match demand. The government of Singapore, for example, offers $370 subsidies to all Singaporeans aged 25 and over to study in hundreds of career-oriented courses. Singapore’s national university also adapted to offer more worker-friendly educational opportunities, including part-time degrees, modular certificate courses, executive education, and free classes for alumni. Denmark, which has a long tradition of continuing education, runs an ‘Arbejdsmarkedsuddannelser’ programme of short courses focused on providing both low-skilled and skilled workers with the skills and qualifications they need. In Sweden, job security councils, jointly managed by the private sector and unions, retrain workers who need to upgrade their skills as a result of automation. Some US states have made community colleges free for residents in order to encourage ongoing skills training.
Some of these programmes and incentives focus specifically on retraining workers whose roles could be replaced by automation. The UK government, for example, has launched a ‘Get Help to Retrain’ scheme aimed at helping adults identify and address skills gaps and job opportunities.,
A number of public-private partnerships focus on ensuring that educational curricula are matched to local and regional employer demand. In the US, Markle Foundation has teamed with the states of Colorado and Indiana, educational institutions such as Purdue University, state-wide employers such as Microsoft, LinkedIn and Walmart, and local small-and mid-sized businesses to match curricula to skills demand from employers. Manufacturing USA, created in 2014 to secure U.S. global leadership in advanced manufacturing, focuses on collaboration between its 14 institutes, their industrial partners, and local school systems and academic institutions to promote and develop the advanced skills needed for the future manufacturing . One of these Institute –ARM – focuses specifically on robotics.
A number of Industry 4.0 Competence Centres established in Italy focus on technology and skills transfer to manufacturers. For example, MADE, headed by Politecnico di Milano, collaborates with 39 technology companies and other Italian universities to provide manufacturing companies in Italy with services including training. The competence centres also enable manufacturers to trial and assess how various technologies could be applied in their specific context. Meanwhile, Germany’s Fraunhofer Institute has partnered with technology companies to develop a Future Work Lab aimed at helping companies and employees experience and prepare for future automation scenarios. The Future Work Lab offers standardised and bespoke training courses in the new technologies demonstrated.
Many private-sector organisations have initiated programmes – often in collaboration with local education institutes – to ensure a supply of relevant skills. Amazon recently announced a $700 million investment to retrain about a third of its American workers in digital and automation skills, including robots. IBM has partnered with 200 public high schools in its Pathways in Technology Early College High Schools (P-TECH) programme providing a six-year program that provides over 100,000 primarily low-income students in 18 countries with ‘career-ready’ skills in scientific, technology and engineering disciplines. Curricula are developed in collaboration with industry partners.
While governments and companies focus on equipping the workforce with skills to use new technologies, makers of those technologies – including robot manufacturers – are working to ensure the technologies are easier to use. Programming interfaces are increasingly intuitive, and many robots can be trained through demonstration. As we describe in our paper Demystifying Collaborative Robots, a new generation of collaborative industrial robots, designed to be integrated into production lines with workers, offer employees in all sizes of company the opportunity to learn and apply basic robot programming and application skills. Most industrial robot manufacturers offer certified training programmes for operators.
As these examples show, governments and companies are responding to the challenge of supporting the workforce in adapting to rapidly changing skills requirements. Various studies indicate that it is middle-skilled workers who are most likely to have to adapt to new job profiles as a result of automation – with 80% of them moving to higher-skilled jobs as a result. However, the OECD sounds a note of caution that not enough is being done to help low-skilled workers, who account for 20% of the OECD’s working population. Low-skilled adults are three times less likely to undertake training than high-skilled workers. Governments will need to do more to engage low-skilled workers in training, through a range of incentives such as mandatory time off for training, and access to free training courses.
Automation continues to gain pace, as the IFR’s recent statistics demonstrate with a 6% increase in sales of industrial robots in 2018 over 2017. Automation technologies such as robots bring many benefits, both directly to workers - whose jobs are less dangerous and more rewarding as a result - and to all of us in our daily lives as we benefit from better healthcare, improved product ranges and a reduction in environmental impact of the food we eat. Armed with the right skills, an increasing number of today and tomorrow’s workforce can ensure that we reap the benefits of automation.
Picture: © ABB
The market value for professional service robots increased by 32% to US$ 9.2 billion in 2018 (over 2017), driven by a 60% increase in unit sales of logistics systems. A 59% increase in the number of personal / domestic service robots sold was dominated by sales of robot vacuum cleaners. The market for personal /domestic service robots reached US$ 3.66 billion in 2018.
The market for both professional and personal / domestic service robots boomed in 2018 with an increase of 61% in professional robot unit sales, generating US$ 9.2 billion, an increase of 32% over 2017. Sales of personal / domestic service robot units increased by 59% though falling unit prices meant this resulted in an increase in sales volume of only 15% over 2017, to US$ 3.66 billion.
The increase in sales of professional service robot units was driven primarily by a 60% increase in the number of logistics systems sold in 2018 over the previous year. Almost 111,000 logistics systems accounted for 41% of the total number of professional service robots sold. Most of these robots are used in non-manufacturing environments, such as warehouses and hospitals, but some are also used in factories to transport parts. The rapid increase in sales of logistics systems is in part due to a boom in e-commerce. Retail e-commerce sales reached almost US $3 trillion in 2018 , almost double the amount in 2015. At the same time, technology advances have expanded the range of tasks logistics robots can perform across a variety of sectors. For example, logistics robots no longer have to follow pre-defined paths but can be programmed with the help of data from sensors, a map of their environment, and algorithms enabling the robot to re-route itself if it encounters an obstacle. Sensors and vision-technologies including machine learning mean robots can be trained to identify and select objects. These technologies are also applied in fixed industrial robots, but the ability to combine them with autonomous guided vehicles means robots can now be programmed to autonomously navigate to, and select, an object – for example to fulfil an order. Robot arms and grippers have also advanced significantly, so that logistics robots can now successfully handle an increasing variety of products including fragile materials.
Inspection and maintenance robots form the second largest category of professional service robots by unit sales, accounting for 39% of new unit sales in 2018. The same technologies that are driving advancements in logistics robots – particularly vision systems and machine-learning, as well as structural improvements that enable robots to enter and move around in very confined spaces, are spurring the adoption of inspection robots in a wide range of sectors and physical environments from factories to oilfields, to underwater inspection on ships.
By sales value, however, medical robots take second place after logistics robots, accounting for 30% of the value of total new sales of professional robots in 2018. Most of the US$ 2.8 billion in sales of medical robots were for surgery robots. However, robot rehabilitation systems, used to help people recover motor skills after accidents or medical conditions such as strokes, were the fastest-growing category of medical robots, with 83% sales growth (in both units and sales volume) in 2018 over the previous year. Given ageing populations in developed economies, strong sales growth of 47% in units sold and 45% in sales value annually on average between 2019 and 2022 is forecast for this category of robot.
Another fast-growing category of professional service robots with a promising future is public relations robots which are used to provide information in shops and public spaces. Though some of these robots are currently used principally for branding purposes, others are functionally efficient – for example guiding visitors in a store to products they have identified through a touch screen located on the robot. Some of these robots allow the shopper to connect via the screen to a remote support agent if the information provided through the touch screen is not sufficient. The sales value of public relations robots increased by 28% in 2018 to just over US$ 158 million, with 40% growth forecast for 2019.
The category personal / domestic robots covers robots used in the home for domestic tasks, entertainment and assistance. Floor- and window-cleaning robots and robotic lawnmowers, together with robotic toys and games, dominate sales. Sales of cleaning robots reached over US$ 2.4 billion, accounting for 67% of personal / domestic service robot sales value – a growth of 24% over 2017. It is projected that sales of robots for domestic tasks (vacuum cleaning, lawn-mowing, window cleaning and other types) could exceed 17.6 million units (valued at US$ 3.3 billion) in 2019 and 55 million units with an estimated value of US$ 9.7 billion in 2022.
The sales value of robot toys – the other primary type of personal / domestic robot – declined by 1%, though unit sales increased by 8%. This market value of this sector is expected to increase by an average of 10% per year from 2019 to just under US$ 1.7 billion in 2022.
The market for robots for elderly and handicap assistance is currently small, accounting for only 1.3% of sales value of personal / domestic service robots in 2018. However, this market is expected to increase by an average of 29% per year from 2019 to a value of around US$ 126 million in 2022. As in the professional service robot sectors, technology advancements in robot mobility, end effectors (grippers) and vision technologies are driving adoption of robots in this sector.
Unlike the industrial robot sector, which is dominated by Japanese, Korean and German manufacturers, the US and Europe drive service robot development. In 2018, 44% of all service robot manufacturers are European companies, 35% are American firms, and 21% are Asian manufacturers. Around half of all logistic system manufacturers are European companies, while US manufacturers have a strong presence in medical and defence robots. Asian manufacturers are the dominant producers of robots for domestic tasks and entertainment.
Start-up companies play an important role in the development of the sector, accounting for 25% of service robot companies. Larger companies are entering the service robot market through acquisitions – the most well-known example being Amazon’s acquisition of Kiva Systems in 2012. Production clusters are located quite differently to those for industrial robots, often near to centres of expertise in advanced software development, for example Silicon Valley.
The dynamism of the service robot sector, illustrated by strong growth in 2018, is set to continue. The sales value of professional service robots is estimated to increase by 45% on average per year between 2019 and 2022, reaching a total of about US$ 38 billion in 2022. Meanwhile, the sales value of personal /domestic robots will increase by an annual average of 35% in the same period to just over US$ 11.5 billion in 2022.
Global sales of industrial robots reached a peak of US $16.5 billion in 2018, an increase of 1% over 2017. The number of robots sold increased by 6% to a record 422,000. China continues to be the leading market for industrial robots, despite declining sales in 2018. Germany and Italy led strong growth in Europe, while the United States leapfrogged Korea to become the third largest industrial robot market globally.
In 2018 sales of industrial robots reached a new record of US $16.5 billion dollars in 2018, an increase of 1% over 2017. The number of robots sold increased by 6% to a record 422,000. There are now 2.4 million robots at work globally and the IFR forecasts almost 4 million robots in operation globally by 2022.
Economic and geopolitical turbulence led to caution over capital investments, resulting in lower-than-expected new sales in 2018. “The automotive and electrical-electronics industries had a difficult year. Structural shifts in the automotive industry with the move to hybrid and electric vehicles, combined with the impact of the US-China trade conflict made their mark,” commented Junji Tsuda, IFR President. “However, some geographies, including those such as Japan and Germany, that have a historically high rate of robot adoption, showed remarkable double-digit growth in 2018.”
The automotive industry remains the largest adopter of robots globally, accounting for almost 30% of total supply, an increase of 2% over 2017. The electrical / electronics industry, which was set to overtake the automotive industry in global share of sales, held back on capital investments in 2018, most probably as a result of uncertainty around US-China trade tension. The share of 2018 sales of the electrical / electronics industry receded to just under 25%.
Robot adoption continues to diversify to new industries, driven by increasing flexibility of deployment. New technologies such a broader range of grippers and more sophisticated sensors continue to expand the range of tasks robots can perform, from identifying and picking objects from unsorted bins, to sophisticated polishing applications. Robot installations in the food and beverage industry have almost doubled since 2013 for example. Other non-manufacturing branches such as construction and utilities also demonstrated strong growth rates from a historically low base of robot adoption.
More intuitive programming interfaces, and robots that are designed to work alongside humans (collaborative industrial robots), make robots an increasingly viable capital investment for all sizes of company. The IFR began tracking sales of collaborative industrial robots in 2018 and recorded 14,000 collaborative robot sales – 3.24% of total sales for the year. Though low, this figure represents an increase of 23% over 2017 and the IFR anticipates strong growth of collaborative industrial robots going forward.
Asia remains the world’s largest industrial robot market, with China accounting for 36% of new sales in 2018. Sales in China declined by 1% over 2017, influenced in part by trade tensions with the US. However, 2018 robot sales in China were still more – at 154,000 – than in Europe and the Americas combined. Chinese robot manufacturers increased their share of sales in China by 5 percentage points over 2017, accounting for 27% of industrial robots sold in the country, reflecting the government’s focus on developing domestic value-added technology sectors including robotics.
Robot sales to Japan increased by 21% in 2018 – a remarkable figure given Japan’s economic woes during 2018, and the fact that Japan already has the third highest proportion of robots to workers in manufacturing industries globally. Two thirds of new sales went to the automotive and electrical / electronics industries. Almost all of the 55,240 robots sold in Japan were also manufactured in Japan. Japanese robot manufacturers supply just over half of the world’s robots.
Germany and the United States – the fifth and third largest industrial robot markets respectively - also saw strong sales growth, at 26% and 22% respectively over 2017. The automotive industry accounted for a significant percentage of sales in both countries (59% and 38% respectively) but while sales to the automotive sector in the United States declined in 2018, they increased by a stunning 73% in Germany, following three years of declining sales to the sector. In the US, strongest growth came from other sectors. Robot sales to the food and beverage industry in the US, for example, increased by 72% in 2018 to 2754 new robots sold – nevertheless still only 18% of sales to the US automotive sector. Robot sales in Korea declined for the third year running, driven by low demand from the electronics industry, which had a tough year in 2018. Korea moved to fourth largest industrial robot market in 2018 for the first time, behind the US. Nevertheless, installations in Korea have increased by 12% on average per year since 2013.
In Western Europe, growth of 19% was driven by Germany and Italy. With 2018 sales growth of 27%, Italy is Europe’s second largest industrial robot market. Growth in Eastern Europe declined, apart from in the Russian Federation and Poland, both of which reported sales growth of over 40% compared with 2017.
Looking ahead, the IFR predicts a flat 2019, driven by economic uncertainty, with robot sales of 421,000 units. However, assuming a more stable global economy in 2020, the IFR forecasts a healthy average annual sales growth of 12% on average 2020 to 2022.
Russia is not generally associated with the use or manufacture of robotics. While it’s true that the uptake of robots in the Federation is lower than in in Europe and Asia, a number of trends in both the indicate this could change over the next 5 years.
Five trends are driving an increased focus on robotics in the Russian Federation. First is a government focus on acceleration the development and application of digital technologies, including robotics. Second is the booming demand for educational robotics. Third, Russian robot manufacturers have set their sights on the service robot sector. Fourth, there is a growing market for industrial robots. Finally, Russian robot suppliers are focussing on development of robot applications and business models to enable small and medium-sized businesses (SMEs) to invest in robots.
The Russian government, in common with most of the world’s governments, has put emphasis on digitalisation as a driver of economic growth. The state program “Digital economy of the Russian Federation” , launched in 2017, includes robotics, and several robotics initiatives within the programme are expected to be initiated in 2019. For example, the Russian Association of Robotics (RAR) is working on a strategy for the development of the Russian robotics industry with the support of the Russian Ministry of Trade and Industry. Second, the government plans to introduce regulation on AI and robotics aimed at clarifying legal issues regarding the use of robots and AI. The aim is to stimulate the development and adoption of these technologies by minimising legal risk. In 2018, the government commissioned research and counsel on the approaches to the regulation of robots, similar to the European Robolaw project. This year, the government has developed a roadmap for research and development on advanced robotics, defining which priority technologies will be state funded. Measures to support technology developers are now in planning.
In 2017 the education sector was the heaviest adopter of service robots in Russia, accounting for 31% of service robots sold by the 10 leading service robot companies tracked by RAR, and 10% of sales of industrial robots to the Russian Federation. The education market covers a wide range of robotics technologies including: LEGO constructors and Russian variants; educational kits with neuro-interfaces; drones for pilot training skills; mobile platforms for testing algorithms for unmanned motion and industrial robots for teaching students at universities and technical colleges. Courses in robotics are offered for children, and there are free online courses available to teachers of these courses. There are robotics clubs in public institutions of further education as well as fee-based clubs.
To some extent, the boom in the development and adoption of educational robots can be compared with the impact of the introduction of compulsory computer science courses in the USSR in 1985, which resulted in a generation of programmers who created Russian IT giants such as Yandex (search engine), Kaspersky (anti-virus software) and Mail.ru (email and social network platform). In the case of robotics, interest is driven by a desire by parents to ensure their children are equipped with the right skills to prosper in the job market. Russian media fuel this focus through stories on how robots and AI will change the nature of jobs in the future.
Though Russia does not have a foothold in the market for industrial robot development, it is rapidly gaining ground in the booming service robot sector. There are more than 100 service robot companies in Russia. The top 10 companies, tracked by RAR, are doubling revenue annually and increased staff by 30% in 2018. In addition to domestic sales, the top service robot companies also enjoy strong export sales. Promobot, which develops information and assistance robots for public spaces, derives 65% of revenues from export sales in 33 countries in North America, Europe, Asia-Pacific and Africa. Alpha-robotics, another Russian developer of robots for public places, sells robots in 10 countries, with exports accounting for 30% of sales. ROBBO, a manufacturer of educational robotic kits based on open source software, supplies the product to 12 countries, such as Finland and Thailand.
ExoAtlet, which produces exoskeletons for rehabilitation, is actively developing in the Asian region. In 2016, the company Exoatlet Asia was registered in South Korea, and the company was licensed to provide medical devices. Exoatlet plans further expansion in China, Japan, Singapore, India, Malaysia, Thailand, Vietnam, and the United States.
Geoscan, which supplies complete solutions for unmanned aerial vehicles (UAV), exports equipment to 15 countries and its software is used in 130 countries. The company supplies a wide range of technologies used in sectors ranging from precision agriculture; geomagnetic exploration and; entertainment. In 2018, geomagnetic exploration of the region of Yaktutia using Geoscan drones led to the discovery of over 300 million tons of iron ore.
Russian service robot company VIST Group is involved in Russia’s first completely autonomous open mining project aimed at reducing operating costs and improving safety. The aim is for all of the machinery involved, including excavators, loaders, drilling rigs and railway transport, to be run autonomously. VIST is developing robotic trucks in collaboration with various manufacturers of trucks and mining equipment.
Harsh natural conditions in Russia make it the ideal testing ground for unmanned transport. The Russian Venture Company, a state fund of funds and a development institution in the Russian venture capital market, is holding a “Winter City” competition to test unmanned vehicles in the Russian winter. Thirteen teams compete to see which can drive 50KM in 3 hours in conditions including low visibility, absence of road markings, other traffic, and unexpected traffic interference. The contest final will be held in December 2019 and the winner will receive 175 million rubles.
The low density of robots in Russian industry - 4 robots per 10,000 manufacturing workers in 2017 compared to 710 robots per 10,000 manufacturing workers in Korea - indicates great growth potential. In general, Russian companies are just starting to explore the benefits of industrial robotics and learning to work with automation technologies. A lack of robot integrators to assist in implementation is hindering adoption. University and colleges tend to be focused on mechanics and robot design. These institutions have recognized, and are addressing, the need to expand to focus additionally on robot programming and implementation. Russia’s traditional strengths in mathematics and software programming are make robot programming a promising field for higher education institutes.
Currently, around 15 industrial robot manufacturers, both foreign and domestic, dominate the Russian market, with around 10 robot production projects underway. Given Russian labor costs are lower than In Europe or China, Russian manufacturers hope to compete on price. There are around 80 robot integrators in the country, but most do not have experience with large projects, for example in the automotive industry which accounts for 40% of robot sales in Russia. Metallurgy and machine building are the other key applications of robots. However, 2017 saw significant interest in robotics by the food industry, which is experiencing a period of growth and modernization, including automation.
To date, industrial robots have been used for the automation of mass production and have been too expensive for small-series or custom manufacturing because the robots need to be constantly re-programmed and re-calibrated for each new or non-standard activity.
This is changing through the use of collaborative robots and other technologies to automate programming. Robots are also being offered on a leasing or fee-per-use model – Robot as a Service – removing the requirement for initial capital investment which can be prohibitive for small companies. There is growing interest in this trend among Russian companies, and Russian robot suppliers are also focusing on delivering solutions. For example, ABAGY has developed a solution that automatically converts 3D CAD drawings and technological instructions into instructions for robots, without any user programming. ABAGY offers ready-to-use robotic cells that perform welding, cutting, painting, milling, assembling and polishing. The company configures and supplies robotic cells, provides installation, integration and maintenance and charges only for work done (e.g. length of weld or area painted).
The expanding range of robot capabilities combined with an increasing awareness on the part of Russian manufacturers of the benefits of automation led to robot installations in the Russian Federation almost doubling in 2017 over 2016. Historically low adoption rates provide huge opportunity for further growth.
Picture. © Promobot
Manufacturers are increasingly turning to software-defined manufacturing (SDM) – a technology model in which manufacturing software and hardware are decoupled - to substantially optimise product design and production.
BMW i Ventures’ recent investment in software-defined manufacturing specialist, Bright Machines is just one indication of the potential large manufacturers see to substantially optimise product design and production through this new technology model.
Manufacturing today is defined by increasing product variability and shorter product development and production cycles. For example, the number of combinations of options for the BMW 6 series was 33 times greater in 2015 than in 2008. And Volvo estimates it will have halved the time between the design and start of production of a new car model by 2020 (compared to 2012 level).
The speed with which manufacturers can reconfigure the production to a new run and thus avoid costly machine downtime – which some estimates put at $1.3 million per hour - and expensive inventory storage is critical to maintaining profit margins.
One hurdle manufacturers face is that manufacturing equipment has historically not been designed to deal with a high level of product variance. Manufacturing machines, including industrial robots, have typically required expert programmers working with code specific to individual manufacturers and machines. Once set up, machines have traditionally been expected to continue doing exactly the same task. This remains the case for some processes, but product variability has led to a much higher need to re-configure a machine within a relatively short timeframe.
In robotics, installation and integration into a production cell are estimated to account for up to two-thirds of the overall cost of an industrial robot. The software that instructs the robot’s physical movements is traditionally deeply entwined with the robot hardware that executes the movements. This means that a robot programme for drilling 3mm holes in a metal plate cannot be simply re-installed on a different manufacturer’s robot even if the new robot is supposed to carry out exactly the same task. In addition, manufacturing machines have not been integrated - so a CNC milling machine cannot ‘tell’ a grinding robot that it needs to grind an extra 1mm off a part for example.
This is changing, as machines become easier to re-purpose, and as they become increasingly networked. First, robot programming has become easier, thanks to more intuitive user interfaces, and technology that enables the robot to part-programme itself by registering motion through hand-guiding by an operator. Second, a concept called software-defined manufacturing (SDM) is enabling far more flexible and faster programming not only of individual machines, but also of entire production processes.
In SDM, hardware and software are de-coupled; with the aim of ensuring that machines can be networked and configured quickly, and that code is re-usable across different machines.
SDM offers four main benefits:
Automotive manufacturers are probably furthest ahead in fully implementing SDM. But smaller manufacturers are also taking steps. A German timber manufacturer, for example, has integrated an industrial robot into a production process for producing wooden frames. The robot installs metal studs into the wooden frame and receives information in real time about which stud to remove from which collection station and where in the frame to place it.
Graph: © A. Verl, ISW University of Stuttgart
Experts at the IFR CEO Roundtable held in Chicago on April 8 debated the question of who will win the race on artificial intelligence and robotics.
Artificial intelligence (AI) and robots continue to occupy news headlines. Given the importance of the two technologies to turning around low productivity rates, which continue to hold back economic growth, most countries have prioritised the development of an AI and robotics strategy, and support for national industry champions. As Robert Atkinson, President, Information Technology and Innovation Foundation (ITIF), US, pointed out, ‘countries care about robotics because it’s a source of high paying jobs – so there’s a race to get more of these companies in each country.’ Increasingly, there is a question of which country will win the race for technology dominance. Will it be the US, with its strong track record in software development? Or will it be countries such as Germany, Japan and Korea that have a strong heritage in engineering? And what of China, whose government has put a clear emphasis on robotics as a means to improve the competitiveness of Chinese company though automation?
The IFR 2019 CEO Roundtable, held on April 8 in Chicago, assembled executives from Europe, Asia and the US to debate the issue and look more broadly about what needs to be done to deliver on the promise of AI and robotics for driving much-needed productivity increases.
Panellists agreed that competition in AI and robotics is happening on two fronts – development and implementation. Japan and Europe are leading in robot development and supply according to IFR President and Representative Director / Chairman of the Board of Yaskawa Electric Corp., Japan, Junji Tsuda. While the Chinese robot market is growing fast, the majority of robots supplied to China come from other countries. Atkinson added that Vietnam, China and Singapore are investing heavily in robotics, but the US lags behind.
Panellists agreed that the pace of robot implementation is still relatively slow, and that the government has a role to play in accelerating adoption. Byron Clayton, CEO of Advanced Robotics for Manufacturing (ARM), US, pointed to the German model of investing in applied research institutes such as Fraunhofer that work with companies to get cutting-edge technologies on to the factory floor. He called for more investment by the US government in supporting companies in adopting robotics and AI. ‘The government needs to invest in reducing risk for the market,’ said Clayton. ‘For small-to-medium-sized companies in particular, the biggest barrier is that investment risk.’ Tsuda agreed, adding, ‘If we can apply AI to make robots easier to set up and use for SMEs, it will be a game-changer.’
The panellists agreed that the automation of service industries is key to improving economic productivity and per capita income. As Atkinson put it, ‘we’re in trouble if we can only automate manufacturing.’ However, Tsuda pointed out that more development is needed in robot dexterity. ‘If the application just needs a robot arm, we can do anything, but if we need a hand, that’s decades away.’ The healthcare sector was cited as a promising field for robot implementation to assist workers but, as Thomas Visti, CEO of the Danish company Mobile Industrial Robots, pointed out, ‘Two things are slowing down implementation: One is a lack of experience in working with robots, but the other is the very slow sales process – it takes years before decisions are made on tenders. China is much faster in adopting robots in the healthcare sector.’
The panellists agreed that AI will play an important role in enabling the expansion of robot implementation into new market sectors, but that the integration of AI into commercially available robots will take far longer than most people think. ‘Significant numbers of policy-makers, thought- leaders and advocates fundamentally buy into the idea that it´s only a matter of time – 10 to 15 years – before robots can do everything. That’s utter nonsense!’ said Atkinson. Even in the automotive sector, which until recently has been the largest adopter of robotics, AI is not yet widely applied. Henry Sun, Director of Strategy, Guangzhou MINO Automotive Equipment Co, China, commented that in China, ‘Most OEMs are still installing connected equipment that generates data, and you need that foundation before you can start applying AI.’ Tsuda sees huge potential for AI in digital twin applications in manufacturing. ‘AI can provide data on the real world – sounds, vibrations – that can link the cyber world to the real world and make robots more efficient and easier to use.’ All four panellists agreed that autonomous vehicles will not be in widespread use within the next five years. Sun believes that,’ We’ll see some specific use areas in geo-fenced areas, but the liability is currently too great for OEMs to take on.’
Panellists agreed that linking the cyber world to the physical world brings security issues that, according to Visti, are, ‘a huge topic – important for customers, and a learning period for us.’ Atkinson believes that government has an important role to play in reducing cyber-security risk, for example by publishing standards and then fining companies that do not adhere to them.
The group agreed that a skills gap is hindering the growth of the robotics sector, in both development and implementation. ‘It’s challenging to find highly-qualified people in AI for robotics’ said Visti. Sun agreed that the gap is in AI skills rather than robotics in China. ‘Young people are excited to be working in robotics, but it’s more difficult to find the AI experience.’ Atkinson felt the US government will need to do more to encourage students. ‘In the US, most of the students in computer science and engineering faculties are from out of state, or outside the US because there isn’t enough federal funding of state universities, so they need out-of-state income. The government also needs to do more to train manufacturing line workers to do some basic AI training so they can up-skill.’ Clayton added, ‘We need to hire for potential, not for experience because this is such a new field. Then we need to design pathways to train people’. Visti added that the private sector has a responsibility to invest in training the workforce of tomorrow. ‘In the short term, it might be hard to get the return on AI, but we need to create the opportunities – and young people are keen to move into robotics and AI’.
Faced with the question of which country will win the race for robotics and AI, Tsuda concluded that, `the AI community is open and shares new logic (programming)´. And the field of application of robotics is so broad that, as long as we can accelerate the pace of implementation, everyone will be the winner!´
Picture. © Carsten Heer
2018 sales of industrial robots were the highest on record, reaching 384,000. The US and Europe showed strong sales growth. China continues to dominate robot sales, accounting for 35% of all industrial robots sold in 2018.
Globally, sales increased by 1% in 2018 over the previous year, considerably lower than expected. The main reasons for this were declining sales to the automotive and electronics industries which accounted for 60% of global sales of industrial robots in 2018. Both these sectors are under pressure. Car sales in China - the largest market - declined, in part due to uncertainty over the development of the electric car market. The consumer electronics sector is also under pressure – demand for smartphones has flattened, for example, for the first time in many years. As a result, manufacturers in these sectors are likely holding off new capital investments such as robots, resulting in a 6% decrease in robot sales to the automotive sector and an 8% decrease in sales to the electrical and electronics sectors in 2018 over the previous year.
Despite challenges in the automotive and electronics sectors, 2018 saw strong growth in industrial robot sales in the US and Europe. Sales in Europe grew by 7% year-on-year. Sales of industrial robots in Germany, the fifth largest robot market, grew by 30% over 2017. In contrast to other countries, robot sales to the automotive industry in Germany more than doubled in 2018.
2018 sales in the US grew by 15% - almost double the average annual increase of 8% between 2012 and 2017. The slowdown in robot adoption in the automotive manufacturing industry in the US was somewhat offset by a 9% increase in robot sales to automotive parts manufacturers. Over twice as many robots (9,939) were sold in the US to automotive part manufacturers than to manufacturers of motor vehicles.
China continued to dominate robot sales. Over 133,000 robots were sold in China in 2018 – more than the next three largest markets (Japan, US and Korea) combined. Robot sales in China were 4% lower than in 2017. This is in part due to a decline in sales to the automotive and electronics sectors in China.
Although automotive and electronics sectors accounted for 60% of global sales, 2018 sales showed diversification in robot adoption into sectors which have, to date, been slow to automate. Sales to the food and beverage sector grew by 24% globally, and by 64% in the US. Sales of robots to the pharmaceutical and cosmetics sectors grew in the US by nearly 60%. These strong growth rates reflect technical developments in robotics, in particular in grippers, vision technologies and ease-of-programming and re-tasking, which make robot adoption increasingly economically viable in these sectors.
China saw strong growth in adoption in the metals and machinery, and plastics and chemicals sectors. Much of this demand was serviced by Chinese robot manufacturers, which have set ambitious targets for fulfilling domestic demand for robots.
Like any other capital investment, robot sales will continue to be affected by global economic and geo-political trends. For example, uncertainty over US trade policy with respect to the North American Free Trade Agreement might have contributed to declining robot sales in Canada and Mexico in 2018. Over 50% of robot sales in the Americas region are to automotive manufacturers, which were subject to uncertainty over tariffs during NAFTA negotiations in 2018.
However, the IFR predicts a continued positive outlook for robot adoption globally. China, the leading market for robots, has an extremely diverse manufacturing sector which protects it to some extent from geo-political shifts. Though China is the world’s largest automobile market, automotive manufacturing only accounts for 7.5% of China’s manufacturing sales. There are over 100 manufacturing sectors in China, many of which have only just begun to automate.
Robots are increasingly versatile and applicable to new manufacturing sectors, and to new tasks in sectors such as automotive manufacturing that have already automated primary production. For example, collaborative industrial robots are enabling automotive manufacturers to support workers in completing final assembly tasks. Collaborative robots work alongside workers, taking on the heavy lifting and tedious tasks that often lead to muscle strain and chronic back complaints for their human colleagues.
More comprehensive 2018 sales figures, and updated guidance for 2019 – 2022, will be available in October.
Since 2013, China has been the world’s leading robot market. China now accounts for almost a quarter of all the industrial robots installed globally – more than in any other country. In 2017, robot sales to China increased by 59% over the previous year, accounting for 36% of global sales of industrial robots.
The International Federation of Robotics (IFR) predicts that China will be the main market driving a 14% global annual average increase in sales of industrial robots to 2021. In 2021, China will account for almost half of all new sales of industrial robots and over one third of all installed industrial robots globally. Over 1.3 million robots will be in operation in China at this point.
Concerns over a slowdown in automotive production and sales in China – and more recently, a dip in overall manufacturing demand – have raised the question of whether China’s robot market will achieve this forecast. The Chinese Robot Industry Alliance believes that it will. Here are four reasons why:
1. The development of the Chinese robot market does not primarily depend on the automotive industry
Industrial robot growth has historically been driven heavily by sales to the automotive industry. But that is longer the case. First, the automotive market is relatively saturated. There are over 500 robots per 10,000 employees in China’s automotive manufacturing sector. This compares with less than 50 robots per 10,000 employees in other manufacturing sectors. Since 2016, the electrical and electronics sector has bought more industrial robots than the automotive industry, and this sector continues to boom, with double-digit growth in high-end electronics in 2018.
The strength of China’s manufacturing industry is its high degree of diversification. The automotive industry accounts for only 7.5% of China’s manufacturing sales. In fact, over 100 different manufacturing industries in China use robots and most of them have only just begun to automate, for example leather and fur manufacturing, wood processing, machinery and equipment repair, pipeline transportation and furniture manufacturing. There are also promising new markets that the Chinese government has prioritised for development, such as medical devices.
2. Rising wages and labour shortages are making robots economically viable, even for small businesses
Around 84% of China’s manufacturing companies are small businesses. These companies had little incentive to automate while labour costs were low. But that has changed. The average manufacturing wage increased by over 57% between 2010 and 2017 in China – versus an increase of around 15% in US over that time. Meanwhile, China’s working age population is shrinking – by 46 million between 2011 and 2018 according to China’s National Bureau of Statistics. Competition for qualified workers is fierce in a wide range of sectors. The Zhaopin CIER index, which tracks the number of applications for job openings, showed that there were over 20 times more open positions for machine operators than applicants in 2018. Companies in prime manufacturing centres where wages are high can generally recoup the capital cost of investments in robots within less than two years. An increase in robot adoption is not associated in China with fears of robots taking jobs. To date, manufacturing employment has increased alongside automation. Manufacturing employment increased by an average of 15% annually between 2012 and 2016, The number of robots per 10,000 workers tripled over that period. CRIA recently carried out research which showed that only 2.2% of robots installed in China replaced workers who left their jobs, while the growth in robot companies and the demand for workers to operate and maintain robots has increased employment.
3. ‘Made in China 2025’ will drive robot market growth
The Chinese government’s ‘Made in China 2025’ policy aims at improving the competitiveness of Chinese companies though automation. As part of the strategy to achieve this, the government’s Robotic Industry Development Plan gives a target robot density (the number of robots per 10,000 workers) of 150 by 2020. Meeting that target would mean the adoption of more than 250,000 robots. CRIA forecasts new sales of 625,000 by the end of 2020, meaning this target will be easily met.
4. Strong focus on domestic market
In addition to improving the competitiveness and productivity of traditional manufacturing sectors, the Chinese government also wants to move up the manufacturing value chain away from commoditised components towards semi- or fully-finished products, including those in promising new sectors such as electric vehicles and medical devices, for which there is strong domestic as well as foreign demand. In many of these sectors, robots are critical to ensure quality and increased productivity. The government also includes industrial robots in the list of sectors in which it would like to see increased domestic production. Robot manufacturers want 70% of the robots supplied in China to come from Chinese robot manufacturers by 2025. This is a steep target given that in 2017, only one quarter of industrial robots sold in China were made by Chinese robot manufacturers. However, Chinese robot manufacturers have the advantage of being close to the market and understanding the needs of sectors that are only just starting to automate, such as sanitary ware and furniture manufacturing. In order to ensure a place high up the value-chain, Chinese robot manufacturers will need to offer expertise in the range of technologies driving robot development and not just produce base robotic hardware. Many are forging close links with universities and research organisations in order to secure expertise in areas such as robot software, vision technologies, sensors and artificial intelligence.
Opinion is divided on the impact of trade tensions between the US and China on the robotics sector. Direct trade in robots is unlikely to be significantly affected, since Chinese robot manufacturers are primarily focused on the domestic market. The Chinese government has not announced any levies against imports of robots from abroad. In any case, most large International robot manufacturers supplying the Chinese market produce in China.
A broader question is whether Chinese manufacturing sectors that are reliant on exports to the US will reduce capital investments – including in robots – while they wait to see how discussions between China and the US progress. China’s electronics sector, for example, exported about 48% of production to the US in 2017. The evidence from both the Caixan purchasing managers’ index, which tracks activity among private light-industry manufacturers in China, and, the Chinese National Bureau of Statistics’ PMI, which tracks heavy industry, points to cautious optimism from the sector. Both indices went over the important 50 threshhold (which marks the cut-off between growth and recession in manufacturing) in March for the first time in months.
Given the breadth of China’s manufacturing sectors, and the strong focus of improving the productivity of the domestic economy, CRIA believes that trade discussions will have limited, and short-term, impact on the rapid growth of China’s robot market. A more pressing concern is the impact a more general global economic slowdown will have on China’s manufacturing sector. This is hard to predict, in part because it depends on the government’s response. But the combination of the government’s focus on automation with the ongoing increase in manufacturing wages and labour shortages imply that even with some economic contraction, the prospects for China’s robot market remain positive.
Picture: © CRIA
At a factory in Switzerland, a robot navigates its way across the production floor, re-routing itself to avoid an unexpected stack of pallets, before arriving at its destination – a cutting machine which it loads with steel rods. It then moves on to a new workstation where it selects parts from a table and feeds these into a tooling machine. The robot stops when an employee approaches to inspect progress and re-starts automatically when the worker walks away.
This scenario is becoming increasingly common in factories and warehouses around the world through the combination of a collaborative industrial robot arm mounted on an advanced autonomous mobile platform. It reflects recent technology developments in both Automated Guided Vehicles (AGVs) and industrial robots.
While AGVs have been transporting materials around factories and warehouses for many years, they have traditionally relied on fixed, pre-programmed routes. Now, however, autonomous mobile platforms are equipped with software, cameras and sensors that enable them to establish their position against a map of their environment, adjusting course on the fly if they encounter an obstacle and stopping if a worker enters their designated safety area.
Industrial robots traditionally operate behind fences and must be automatically shut down when a worker has entered the designated safety area and re-started manually when the worker has exited. Newer collaborative industrial robots, designed to perform tasks alongside or in direct interaction with workers, can slow and stop when a worker approaches and enters the designated safety area, re-starting automatically as the worker moves away. Depending on the application, these robots might not require fencing or other safeguarding.
Combining these two technologies offers enormous promise for manufacturers and logistics firms to automate the repetitive and physically stressful tasks of fetching and carrying heavy parts and feeding machines. This frees up workers to focus on higher-value tasks requiring levels of dexterity, responsiveness and planning that robots cannot provide.
The combination of a mobile platform and a lightweight collaborative robot arm is one example of an industrial mobile robot (IMR). There are other permutations. For example, large industrial robot arms are used on mobile platforms to polish aircraft bodies. An autonomous mobile platform can be considered a type of IMR even without a robot arm if the platform has a sufficient degree of autonomy. And an industrial robot arm, if integrated with a non-autonomous mobile platform such as an AGV, becomes a type of IMR through the presence of the robot arm. An IMR may have been designed as one unit, or it may a combination of a separate industrial robot and mobile platform.
Currently there are well-regarded existing standards for both AGVs, and for industrial robots and robot systems. These standards include, for AGVs, the U.S. standard B56.5 and the International Organization for Standardization (ISO) 3691-4; and for industrial robots and robot systems, R15.06 in the U.S., the national adoption of ISO 10218-1,2. However, neither standard fully addresses the current state-of-the art of robot mobility. R15.06 was developed at a time when industrial robots were bolted in place, not mobile. B56.5 was developed around the capabilities of devices that did not possess sufficient autonomy to operate safely away from their predetermined paths.
When the two technologies are combined in an IMR, there are instances where the requirements for a particular operation are addressed differently in each set of standards and it is unclear which standard prevails. For example, the re-start requirements following a protective stop are different between the two standards. R15.06 requires that, except in a collaborative application, the industrial robot must be re-started by a human operator from outside the robot cell; the robot is not permitted to re-start automatically. This ensures that the operator has exited the hazardous area before re-start can occur. On the other hand, B56.5 states that when an AGV encounters an obstacle — for example, if a person steps into its path – it is required to come to a stop, but when the obstacle is removed it can re-start automatically along its path. It is this type of conflict that R15.08 aims to resolve by providing a unified standard for IMRs.
The R15.08 committee was formed in 2016 and its members are experts in both the B56.5 AGV standard and the R15.06 industrial robot standard. Though nominally a U.S. standards-development committee operating within the American National Standards Institute (ANSI) framework, R15.08 includes members of the Canadian Standards Association and many of the committee’s members are also involved in the work of the International Organization for Standards (ISO) Technical Committee (TC) 299, Robotics. The Industrial Robot Safety group within the ISO Robotics committee will consider if and how to incorporate R15.08 content into the updated ISO 10218 guidelines for collaborative robot applications.
The committee’s first task was to determine the scope of R15.08. The consensus was to include ground-based mobile robots for use in an industrial environment, which possess a degree of autonomy sufficient to plan their own routes to a destination and re-plan on the fly if an obstacle is encountered.
The R15.08 standard will be published in three parts. Part 1 will specify safety requirements for manufacturers of industrial mobile robots; Part 2 will describe requirements for integrators who are working to design, install, and integrate a safe system of mobile robots into a user’s facility; and Part 3 will define safety requirements for the end-user of industrial mobile robots. The committee’s goal is to publish Part 1 in 2019, followed by Part 2 and Part 3 as these are completed.
Picture: © Stäubli
Traditionally, industrial robots and workers have been separated, with robots performing tasks such as welding, painting, moulding plastics and palletizing. Industrial robots working at high speeds and often manipulating heavy, sharp tools and objects, have typically been fenced. Only authorised workers with special keys have been able to enter the robot cage, after power has been turned off – and only these workers are authorised to re-start the robot on exiting the cage.
A new breed of robots is now enabling manufacturers to use robots alongside workers in production lines where some tasks can be automated, but others either cannot, or are more productive when performed by humans. These robots slow down or stop when workers are near, and re-start automatically when the worker moves away. Many have force-limiting technologies and other design features that ensure they cannot harm a worker if a collision occurs.
Though the market for collaborative robots is highly promising, forecasts on its development are often over-hyped. The IFR will publish statistics on the supply of collaborative industrial robots in 2019, but estimates that in 2017, only 4% of the 381,000 industrial robots globally installed in 2017 were collaborative. IFR members report confusion among customers on what a collaborative robot is, when to use one, and how to ensure safety. The IFR has therefore recently published a paper ‘De-mystifying collaborative robots’ to clarify. Below are some of the main points:
Collaborative industrial robots are a class of robots that perform tasks in collaboration with workers in industrial settings. The International Federation of Robotics defines two types of robots designed for collaborative use. One group covers robots designed for collaborative use that comply with the International Organization for Standards (ISO) norm 10218-1 which specifies requirements and guidelines for the inherent safe design, protective measures and information for use of industrial robots. The other group covers robots designed for collaborative use that do not satisfy the requirements of ISO 10218-1. This does not imply that these robots are unsafe. They may follow different safety standards, for example national or in-house standards. Robots that work with humans in other commercial or non-commercial settings (for example healthcare, food preparation and in public spaces) are covered by separate ISO norms and will therefore not be included in the IFR statistics on collaborative industrial robots.
Case studies describing some of the current most common applications of collaborative robots can be found here.
A common misconception is that a collaborative robot is by definition a safe robot. As with any other tool however, safety is task-dependent. A collaborative robot wielding a sharp tool or part will be unsafe around workers no matter how slowly it runs. Safety assessments are required for collaborative robot applications as they are for any other industrial machine.
Collaborative robots are already working alongside traditional industrial robots in heavily automated sectors such as automotive and electronics. As technology advances - particularly in the fields of grippers, sensors and vision – we can expect to see adoption of collaborative robots in a variety of new manufacturing sectors such as food processing and in manufacturing of consumer goods such as cosmetics.
Picture: © ABB
According to World Robotics - Industrial Robot Report 2018, recently published by the International Federation of Robotics, Japan is the world’s leading supplier of industrial robots. Japanese industrial robot manufacturers delivered just over half (almost 55%) of industrial robots supplied in 2017 – 39% more than in 2016.
Japan is not only a leading manufacturer and exporter of robots, it is also a leading robot adopter. With 297,200 industrial robots at work in Japan in 2017, Japan had the second highest installed base of industrial robots in 2017 (after China with 473,400 units).
Robots are generally viewed positively in Japan. Some Western commentators attribute this to the ancient Japanese religion, Shinto, in which objects (as well as people and other natural phenomena) are believed to possess a spirit. This is not a commonly-held view in Japan, however. Manga comics and animations have had a much stronger cultural influence on interest in robotics. Robots are often depicted as children’s’ friends in mangas, and the post 1950s generation, who grew up with these mangas, learned about friendship, courage, justice and charity through stories that included robots. Thus, Japanese people tend to have friendly feeling towards robots and I know of a number of robot researchers who began as fans of the famous ‘Astro Boy’ manga.
Cultural influences are of course only part of the picture. There are also clear economic and social reasons for Japan’s leading role in robotics development and adoption. The growth of the Japanese automotive industry is probably the most significant factor influencing the rapid development of Japan’s robot industry. In 1980, Japan became the largest automotive manufacturer globally. Japanese automakers started to use industrial robots in the late 1970s, and robot adoption increased after 1980 with more advanced robotics technologies. That enabled Japanese automotive manufacturers to quickly launch new factories to enable rapid overseas expansion, partly resulting from trade friction between Japan and the United States.
Domestically, robots provided a solution to a shortage of automotive workers including skilled welding technicians. Competition between Japanese robot manufacturers around quality and performance in response to the demands of the automotive industry meant that Japanese robot manufacturers came to occupy a leading position in the global robotics market. Meanwhile, Japan’s lifetime employment system, through which employees have traditionally expected to spend their whole working life at one company, meant that employees were not concerned about the introduction of robots impacting their jobs.
Labour shortages continue to be a driver for robot adoption in Japan, not just in the automotive sector. Japan’s working age population has declined by 13 percent from the peak in 1995 to 75.96 million last year, and a further shortfall is forecast. The introduction of robots is regarded as one of the solutions to this problem, which affects many sectors in Japan. Among these are some sectors where demand for robots is especially high – logistics, nursing and elderly care, agriculture, inspecting and maintaining aging public infrastructure, and ‘behind-the-scenes’ work in service and non-manufacturing sectors. Within the manufacturing sector, the food industry is also starting to adopt robots in response to labour shortages. The state of robot development and adoption in these sectors varies. Logistics is a very promising sector, and one that has already started to automate through robots. Robot adoption in the food industry varies by process – some processes, such as picking and packaging wrapped food, have already been automated with robots, while others still have a long way to go. The extent of robot adoption in agriculture also varies and more time will be needed to meet the full requirements of this sector.
The introduction of robots will therefore happen within a short period of time in some sectors but will require more time in other sectors. I believe, however, that many kinds of robots will play an active role in these fields in the future.
Japanese people are not afraid of robots but consider them as partners. Robots will perform tasks which they can do more productively than humans or which are heavy burdens for humans, and humans will perform tasks which robots cannot. The Japanese government has, through its ‘New Robot Strategy’ published in 2015, set a clear focus on speeding the adoption of robots in sectors with low productivity, particularly nursing, agriculture and infrastructure construction. This strategy of course also creates domestic demand which is beneficial for Japanese robot manufacturers, and this will be a boost to the further development of the robot industry.
One element of the New Robot Strategy is the World Robot Summit (WRS), which the government promotes as venue for showing latest robotic technologies and accelerating research and development of robots in sectors that have not yet adopted them. The theme of the WRS is collaboration between humans and robots. Held as a pre-event to WRS 2020, this year’s WRS exhibition and conference programme attracted 76,374 visitors. In addition, the World Robot Competition attracted over 1,000 entries (126 teams from 23 countries) from young robot researchers and engineers around the world focused on trying to get robots to perform some of the tasks that are so easy for humans but still hard for robots. This is important because, despite considerable hype, robots that can actually perform many of the tasks required in nursing and other service sectors are still in the stage of research and development. The high levels of dexterity and responsiveness required for many of these tasks in which humans interact directly with robots are very different to the demands of the automotive and electronics industries. These sectors are the main adopters of robots today – accounting for over 60% of total shipments of industrial robots in Japan. The requirements of nursing and other service sectors present significant technical challenges for robot manufacturers and integrators. Japan has a long tradition of cooperation between manufacturers and users in pursuit of quality improvements, and I believe this culture will serve Japanese robot developers well as they look to address the challenges presented by these new sectors.
Picture: © JARA
In the newly published ‘World Robotics 2018 Service Robots’ the IFR forecasts a continued boom in sales of mobile robots in logistics. Unit sales of automated /autonomous guided vehicles (AGVs) will increase by 66% in 2018, and the IFR forecasts new sales of US $17.5 billion in the period 2019 and 2021.
The boom in logistics robots is driven in part by technical advances and in part by business model changes in the industries adopting these robots.
Advances in sensors and vision technology mean that robots can now move freely around warehouses and factories, sensing and responding to the movements of people and objects around them, without the need for expensive external infrastructure for navigation. Traditional AGVs are programmed to follow pre-defined routes, guided by floor marking and /or sensors. If these AGVs encounter an obstacle, they must wait until their pre-defined path is cleared before moving on. Today, AGVs can plan and execute an optimal path in real-time, or can follow a pre-programmed path, but calculate and execute an alternative if the way ahead is blocked. This capability enables them to navigate areas in factories and warehouses in which workers move around freely. In hospitals and hotels, autonomous guided vehicles can be loaded and secured by a worker and then sent to a specific location to be unlocked by a staff member or hotel guest with the use of a code supplied when they place the order. AGVs offer substantial benefits for the healthcare sector where nurses, who are in short supply, spend as much as 20% of their workday transporting equipment and medications.
Another mobility trend, not captured currently in IFR statistics, is to fit existing equipment that has previously required a driver - such as a fork-lift truck – with software to enable it to operate autonomously.
Vision and gripping technologies increasingly enable robots to pick and load un-sorted items of different weight, shape and robustness. It’s worth noting, though, that these developments are still at an early stage and there are many picking situations in which human dexterity is required. This is particularly the case when objects are limp or can get stuck or jammed easily. The design of asuitable robot solution needs to take into account the spectrum of objects to be handled.
Rapid adoption of automated guided vehicles is also being driven by changes in the way business is organised. The boom in e-commerce is one of the principle business model changes driving the adoption of AGVs. Perhaps counter-intuitively, e-commerce has driven increases in both automation and job creation. This is because the work of selecting and transporting goods was usually done for free by customers themselves, whereas now logistics companies pay workers to do it. E-commerce has created more logistics jobs than have been lost in physical stores. Economist Michael Mandel reports that in the U.S., 355,000 e-commerce jobs were created between 2007 to 2016 - seven times more than were lost in the general retail sector during that period.
Changes in the way manufacturing is organised is also creating demand for mobile robots. The need to produce smaller batch sizes of an increasing number of product varieties is driving a shift away from production stations that move parts along between machines on a conveyor belt towards smaller production cells with mobile robots transporting parts between them. Fraunhofer IPA has developed a system in collaboration with BÄR Automation in Germany for an automotive manufacturer to transport car bodies freely around the factory floor. The system uses a navigation module developed by Fraunhofer IPA that can read and aggregate data from any type (odometry, radar, RFID, laser and others) and make of sensor. It can therefore be used in any customer set-up without further programming. Some manufacturers are adopting a ‘Just-in-Sequence’ model for supplies in order to reduce the cost of holding parts inventory. The required parts are ordered at the time needed and are transported directly from the loading bay to the production cell. This calls for autonomous guided vehicles that can communicate with scheduling systems and move freely around the factory, since production is planned on the fly. (See the IFR report ‘Robots and the Workplace of the Future’ for more information on how changing business models in logistics, manufacturing and healthcare will drive robot adoption).
A significant advantage of logistics robots is that they can be effectively integrated into digital automation networks, giving manufacturers, logistics and other companies a real-time overview of operations. A robot that is transporting medicines in a hospital, for example, can check inventory for the medicine it has collected. If the number falls below a given value, the hospital’s purchasing software automatically orders a new batch. Data transmitted by the robot enables users to visualise – for example through augmented reality glasses - the AGV’s map and internal systems, meaning a technician can identify a problem and, if necessary, quickly copy a route from one robot to another, minimising time and money lost to machine downtime if one AGV misfunctions.
Robots are increasingly moving out of their cages to provide support to workers in factories, warehouses, hospitals and other workplaces, lifting, fetching, carrying and performing tedious, unergonomic tasks. Mobility is central to the concept of human-robot collaboration, and will be key to future robot adoption, particularly by small-to-medium sized companies that have only just begun to automate.
Automated guided vehicles; autonomous guided vehicles (both shorted to AGV); autonomous mobile robot (AMR) and mobile industrial robot (MIR) are four terms used to describe a mobile robot that transports goods or people without a driver at a place of work. Automated guided vehicle is mostly used to denote a guided vehicle that is programmed to follow a specific path indicated by marks or sensors in the operating environment. The robot cannot deviate from the programmed path.
Autonomous is generally used to imply the use of software that enables real-time intelligent path planning to reach a destination (i.e the vehicle is programmed to be able to calculate and select from a range of options when faced with an unplanned event or obstacle).
An industrial mobile robot is a robot arm that moves in three or more axes, mounted on a mobile base and used in an industrial context (vs. in a public space, for example).
The IFR publishes statistics on Logistics Systems which are automated and autonomous guided vehicles for transporting goods and people in factories, warehouses and outdoor working environments.
Picture: © Fraunhofer IPA
The adoption of industrial robots continues to accelerate, with 30% annual growth in sales in 2017. Over 381,000 robots were sold to production industries in 2017, over twice the number sold in 2013. Over 2 million robots are now at work in industry. That number will almost double by the end of 2021, according to the IFR’s new ‘World Robotics 2018, Industrial Robots’ report.
For many years the automotive sector has been the driver of robot sales to manufacturing. This is changing rapidly. The electrical /electronics (E&E) industry will soon become the dominant sector for robot sales. In 2012, twice the number of robots were sold to automotive manufacturers than to the E&E sector. In 2017, the share of supply to the automotive sector was only 1 percentage point more than the share of sales to E&E firms. By 2021, there will be more robots installed in electronics /electrical firms than in automotive manufacturers (based on 2017 growth rates). It could be sooner, given that technology developments in the automotive industry - such as connected and autonomous vehicles, and electric cars – are driven by electronics. The installed base of robots used to produce electrical/ electronic parts for cars has grown at an average annual rate of 45% since 2012.
Growth in robot sales to the E&E industry is in part linked to the growth of the industry itself. The E&E market was worth €4 trillion in 2016 and is forecast to grow at over 4% per year to 20191. Asia accounted for over 85% of robot sales to the E&E sector in 2017 – not surprising, given the region produces around three quarters of the world’s electronics2. Vietnam – now the second-biggest exporter of smartphones in the world - rose to become the seventh largest robot market globally, spurred by a five-fold increase in robot sales in 2017. An expanding E&E sector is also behind the 52% annual increase in robot sales in Malaysia in 2017. This is good news for job creation in the region. The Asian Development Bank estimates that automation led to a net increase of 33 million jobs per annum in developing Asia over 10 years to 20153.
Another reason for the 33% growth in sales of robots to the E&E industry in 2017 is the expanding range of tasks robots can perform, particularly in the assembly of electronic components and equipment. Robotic automation is an increasingly viable economic proposition for electronics manufacturers, who work under extremely tight profit margins. Robots are used across the entire production cycle – from cutting metal housings to assembling miniature components on boards, applying sealants and adhesives buffing and polishing surfaces, performing quality inspections and packing and palletizing finished products.
Electronics assembly requires very rapid, precise placement of miniature objects that are often fragile. Robots must be able to perform multiple tasks in sequence – such as mounting different types of components on a base plate. Advances in grippers, vision technologies and force sensors mean robots can handle an increasingly wide range of production, assembly and finishing tasks. Robots can, for example, now pick unsorted components out of bins and mount components at odd angles.
Developments in sensors and power-force limiting technologies (that ensure the robot slows down or stops if it comes into contact with a worker) mean robots can now share workspaces with E&E employees. Manufacturers can easily insert these collaborative robots into an existing production line and quickly move them between lines. This flexibility is particularly important in E&E, where product cycles often last only a few months. Robots are also becoming easier to programme, enabling faster re-tasking that can often be done by workers with very little training.
Many manufacturing companies are only just beginning to automate - less than half of European manufacturers have not yet adopted any Industry 4.0 technologies, for example, despite three quarters recognising the potential benefits . Increasing industrial automation will fuel the growth of both the E&E industry, which produces much of the equipment needed for automation, and the robot industry, which enables E&E and other manufacturing sectors to improve efficiency, quality and safety.
1 ZVEI Global E&E Industry Facts and Figures 2018
3 Asian Development Outlook 2018: How Technology Affects Jobs, Asian Development Bank
Picture © ABB
Entertaining as it is to watch robots summersault, it’s important that we remain realistic about what robots really can and can’t do. The real world is bound by safety and product regulations – and of course by the question of whether the robot is economically viable for a company to adopt. Regulatory and commercial decisions need to be grounded in a clear understanding of what’s actually possible today, and a recognition that most technology takes between 10 and 25 years to be adopted at scale.
In commercially-available robotic applications, AI is making most impact in expanding robot mobility and dexterity. Until recently, robots in factories and warehouses have moved along pre-determined routes, guided by signals (magnetic, laser, lidar) from devices installed for this purpose in their environment. Sensors enable these robots to recognise an obstacle and stop to avoid collision, continuing on their route when their path is clear. However, these robots cannot find an alternative route to their goal if the obstacle remains in their path. In contrast, an AI-enabled mobile robot gets from A to B by building a real-time map (or updating a pre-programmed map in real-time) of its environment and of its location within that environment, planning a path to the programmed goal, sensing obstacles and re-planning a path in-situ.
Meanwhile, advances in 3D vision technology - one of the AI technologies making fastest progress – mean that robots can now identify objects even when they are partly hidden by other objects or poorly lit. Machine learning enables the robot to teach itself in a very short time how to pick up an object it has not encountered before, applying the appropriate level of force. The machine learning algorithm continues to improve as it picks.
The combination of intelligent mobility and vision technology is driving a boom in automated guided vehicles (AGVs) and picking robots in warehouses and factories. AI-enabled autonomous vehicles are already at work in factories and warehouses, checking inventories, fetching goods and picking items from bins.
The IFR projects a five-fold increase in service robots in logistics by 2020. However, most picking robots designed for agricultural use are still not economically viable compared to human labour. It is still very difficult for robots to pick objects that have irregular and variable shapes – such as fruit and vegetables – or objects that are not rigid – for example, goods in plastic wrapping. These challenges are being overcome, but what’s less clear is how long it will take for broad-scale adoption.
Another rapidly-advancing area of AI is natural-language processing (NLP). This has wide application in software ‘chatbots’ that can understand and respond to questions and provide information. In robots, NLP combines with mobility to enable mobile information robots that assist customers in environments such as hotels, hospitals, airports and shops. They can answer questions, lead customers to requested products or locations and video-link the customer to a human service agent.
Considerable research is going into applying AI to collaborative robots that are designed to work with humans in factories, hospitals and warehouses to assemble products, lift patients and package goods. AI is not yet widely applied in collaborative robots because enabling the robot to respond on the fly to the situation it encounters brings in a level of unpredictability that is unacceptable in most industrial and commercial settings for safety and quality reasons. We’re unlikely to see robots solely powered by AI algorithms in widescale use on the shop floor anytime soon. What we’re more likely to see is the application of AI algorithms to help robots learn to perform tasks quickly. Once the task has been learned, all or a large part of it can be hard-coded to ensure predictability. This is very promising for small-to-medium sized businesses that work with short production runs as it enables them to set up the robot quickly and train it on a new task as a new customer or production run comes on board. AI can also be used for continuous optimisation of the robot, analysing its motion and recommending changes that, though they may be small, can have large cumulative impact on the robot’s speed, efficiency and energy use. AI can also be used to signal when a robot is about to need maintenance, saving companies the expense of machine down-time.
As AI continues its rapid trajectory, important questions are being raised about how its use should be governed by companies and governments. Specific regulation regarding the use of AI in commercially available robots doesn’t yet exist, and the IFR believes that this would not be productive. Robots are physical machines and as such are already governed by detailed safety standards and regulations - such as the EU Machine Directive and OSHA Guidelines for Robotic Safety in the U.S, and various ISO standards. It makes most sense to incrementally adapt these existing guidelines to reflect developments in robots in specific contexts.
The number of AI start-ups in the US topped 600 in 2016 and 128 robot start-up companies in the US received new funding in the same year. There is no doubt that we are at the start of a phase of rapid expansion in robotics, much of it driven by advances in AI. Software development requires little investment in fixed capital, and in many cases can be rolled out to users with bugs that are fixed on the fly. Robots, on the other hand, require fixed capital investment and are governed by safety standards that mean they must be bug-free and fully predictable when made commercially available. So while we can enjoy the rush of box-office films with humanoid, sentient robots, we won’t be seeing them in factories, warehouses and hospitals anytime soon.
Picture © Shutterstock
‘In the present chapter, I shall enter into some enquiry respecting the influence of machinery on the interests of the different classes of society, a subject of great importance’ wrote economist David Ricardo in 18171. In the two centuries that followed, the machinery changed – from the weaving machines and horses of Ricardo’s treatise, to the tractor, the ATM and now robots and artificial intelligence. But the question remains the same. What is the impact of automation on jobs?
Given machines are intended to replace human labour, the intuitive response is that automation’s impact on employment will be negative. Yet a large body of research concludes the opposite – overall, automation has a positive effect on labour demand. Yes, technology does replace jobs in specific industries over time. At the turn of the 20th century, there were around 12 million people employed in agriculture in the United States. One hundred years later, that number had plummeted to 2 million. But consistently over past two centuries, more jobs have been created overall than destroyed2.
Why is this? First, new technologies create new jobs types – think web designer or mechatronic. Second, automation creates new industry sectors and these may provide more jobs than are lost in sectors that decline as a result. Ecommerce has created sixteen times more jobs in the UK since 2010 than have been lost in retail, for example3. But the most important reason automation has maintained its track record of net job creation over so long is its impact on supply and demand. As Adam Smith noted, ‘the desire for food is limited in every man, by the narrow capacity of the human stomach, but the desire of the conveniences, and ornaments of building, dress, equipage and household furniture, seems to have no limit or certain boundary’4. No boundary except the ability to pay for the desired goods that is. This is where automation comes in, by making goods cheaper to supply. The cost of a television, for example, fell by 98% in the US between 1950 and 2017 and as a result the number of American households owning a television rose from 9% of the population in 1950 to 95% in 1970. This pattern continues across most goods and services until demand is saturated and moves on to new sources of desire. Meanwhile, increased productivity through automation results in wage increases that provide more income to spend on goods and services.
Sceptics argue that recent rapid advances in technologies such as artificial intelligence will reverse this long-run trend of net job creation, with many middle- and high-skilled jobs – such as actuaries, paralegals and equity traders - at risk. An increasing body of evidence contradicts this argument, concluding that less than 10% jobs are fully automatable5. But whilst most job categories are here to stay, many will change, and at a faster rate than in the past, leading to a potential gap between the skills employers want and those employees are able to provide. We’re already seeing evidence of this. Recruitment company Manpower found that 40% of the employers it surveyed in 2017 were having difficulty filling roles – the highest level since 20076 and a study by Deloitte and The Manufacturing Institute predicted that 2 million jobs in US manufacturing will go unfilled over the next decade due to lack of skilled workers7.
Addressing the skills gap will take concerted effort. Most companies are just starting to adopt new automation technologies and find it difficult to predict their future skills requirements. The technologies themselves are still evolving. Close collaboration between companies and higher education institutes will be required to ensure a supply of skills for which there is current and future demand. Most industrial economies have recognised and are responding to this. For example, the U.S., which has over recent years focused on the value of four-year bachelor degrees, is pivoting back towards apprenticeship schemes, many of them partnerships of multiple companies and higher education institutes around the industries relevant to a particular region.
In 1817 Ricardo worried whether machinery would have a negative impact on workers and their wages. Two centuries of technology innovation have not delivered evidence to support this concern. As in the past, the current wave of technological change will alter job profiles. The evidence points to this mostly being in the direction of higher-skilled, higher-paid jobs8. We need more, not less, of the machines, and our focus must be on ensuring current and future workers are equipped to work with them.
1 Introduction to Chapter 31, ‘On Machinery’ from ‘On the Principles of Political Economy and Taxation’, David Ricardo, 1817.
2 For example, this is the conclusion reached by Deloitte economists studying census records on employment in England and Wales for every decade year since 1871 together with Labour Force Survey data, from 1992. Another study on the impact of automation on employment in EU countries shows that automation drove a net increase of over 10 million jobs between 1999 and 2010. See Racing With or Against the Machine? Evidence from Europe. Discussion Paper No. 16-053, ZEW Centre for European Economic Research, 2016. Research by the Asian Development Bank showed that productivity increases due to automation led to a net increase in 33 million jobs per annum between 2005 and 2015 in 12 Asian countries - Asian Development Outlook 2018, Asian Development Bank.
3 And seven times more in the US – see The Age of Automation: Artificial Intelligence, robotics and the future of low-skilled work, RSA, September 2017
4 The Wealth of Nations, Adam Smith, 1776.
5 See A Future That Works: Automation, Employment and Productivity , McKinsey Global Institute. 2017; The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis OECD and; The A.I. Paradox, CISCO and Oxford Economics, December 2017
6 Manpower Group. 2016 Global Talent Shortage Infographic.
7 The skills gap in US Manufacturing 2015 and beyond, Deloitte and Manufacturing Institute, 2016
8 See for example: Explaining Job Polarization: Routine-Biased Technological Change and Offshoring. American Economic Review, Vol, 104, issue 8 pages 2509-26 and OECD Employment Outlook 2017
Picture © YASKAWA
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