The IFR’s use of the term “industrial robot” is based on the definition of the International Organization for Standardization: an “automatically controlled, reprogrammable multipurpose manipulator programmable in three or more axes”, which can be either fixed in place or mobile for use in industrial automation applications. (ISO 8373)
The terms used in the definition mean:
Reprogrammable: designed so that the programmed motions or auxiliary functions can be changed without physical alteration;
Multipurpose: capable of being adapted to a different application with physical alteration;
Physical alteration: alteration of the mechanical system (the mechanical system does not include storage media, ROMs, etc.)
Axis: direction used to specify the robot motion in a linear or rotary mode
Industrial robots can be classified according to mechanical structure:
Cartesian robot: robot whose arm has three prismatic joints and whose axes are correlated with a cartesian coordinate system
SCARA robot: a robot, which has two parallel rotary joints to provide compliance in a plane
Articulated robot: a robot whose arm has at least three rotary joints
Parallel/Delta robot: a robot whose arms have concurrent prismatic or rotary joints
Cylindrical robot: a robot whose axes form a cylindrical coordinate system
Find out more about the different robot types in the file below.
The IFR Statistical Department compiles statistical data on annual installations of multipurpose industrial robots for around 40 countries, broken down into areas of application, customer industries, types of robots and other technical and economic aspects.
World Robotics - Industrial Robots provides global statistics on industrial robots in standardized tables and enables national comparisons to be made. Production, export and import data is listed for selected countries. It also offers robot density, i.e. the number of robots per 10,000 employees, as a measure for the degree of automation.
Significantly improved robot system performances and an increased ease of use open up new automation solutions, many of which are outside the “classic” applications of industrial robots. Furthermore, robot manufacturers and system integrators are increasingly supplying flexible work cells with standard configurations, which can be rapidly integrated into existing production systems for standard applications.
This implies that even small-volume productions can effectively be automated in areas such as parts welding and cutting, flexible assembly and packaging and palletizing. Robot investments are becoming more and more profitable and hence become increasingly widespread within industry.
Case studies on industrial robots can be found here.
Main benefits of robot investments
The reasons why companies consider investing in a robot system differ widely. Some factors include the positive effect on parts quality, increase of manufacturing productivity (faster cycle time) and/or yield (less scrap), improved worker safety, reduction of work-in-progress, greater flexibility in the manufacturing process and reduction of costs.
Main reasons for investing in industrial robots:
Increased flexibility to quickly adapt production and respond to changes in demand and smaller batch sizes
Improved resilience to deal with production peaks and withstand systemic shocks such as COVID-19
Energy and resource efficiency through optimized performance (reducing energy consumption, material waste and increasing yield)
Improved productivity and support for manufacturing employees (Improving quality of work for employees, complying with health and safety rules)
Reducing operating or capital costs
Improving product quality
Increasing production output rates
Save space in high value manufacturing areas
Overall, robots increase productivity and competitiveness. Used effectively, they enable companies to become or remain competitive. This is particularly important for small-to-medium sized (SME) businesses that are the backbone of both developed and developing country economies. It also enables large companies to increase their competitiveness through faster product development and delivery. Increased use of robots is also enabling companies in high cost countries to ‘re-shore’ or bring back to their domestic base parts of the supply chain that they have previously outsourced to sources of cheaper labor.
Collaborative industrial robots are designed to perform tasks in collaboration with workers in industrial sectors. The International Federation of Robotics defines two types of robot designed for collaborative use. One group covers robots designed for collaborative use that comply with the International Organization for Standards 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.
There is considerable variance in the types of collaborative robots meeting the above specifications, and the level of contact between robot and worker in collaborative applications. At one end of the technical spectrum are traditional industrial robots operating in a separate workspace that workers can enter periodically without having to shut off power to the robot and secure the production cell beforehand – a time-intensive procedure that can cost thousands of dollars per minute of machine downtime. The robot’s workspace can be fitted with sensors that detect human motion and ensure the robot works at very slow speeds or stops when a worker is within the designated workspace. At the other end of the spectrum are industrial robots designed specifically to work alongside humans in a shared workspace. Often referred to as ‘cobots’, these robots are designed with a variety of technical features that ensure they do not cause harm when a worker comes into direct contact, either deliberately or by accident. These features include lightweight materials, rounded contours, padding, ‘skins’ (padding with embedded sensors) and sensors at the robot base or joints that measure and control force and speed and ensure these do not exceed defined thresholds if contact occurs.
The market for collaborative robots is still in its infancy. End-users and systems integrators are still gaining experience on what works and doesn’t in the design and implementation of collaborative applications. Technology developments in sensors and grippers hold promise for expanding the range of actions that the robot end-effector can perform. Programming interfaces will continue to become more intuitive, not just for cobots, but also for traditional industrial robots.
In 2019, about 4.8% (18,000 out of more than 373,000) industrial robots installed, were cobots, an increase of 11% over 2018.
Artificial intelligence in robots gives companies new opportunities to increase productivity, make work safer, and save people valuable time. Substantial research is being devoted to using AI to expand robot functionality. Commercially available applications include the use of AI to:
Enable robots to sense and respond to their environment: This vastly increases the range of functions robots can perform.
Optimise robot and process performance, saving companies money.
Enable robots to function as mobile, interactive information systems in numerous settings from public spaces to hospitals to retail outlets, saving individuals time.
The IFR has identified five common scenarios in which robots are connected within broader automation strategies:
Automated production: Linking the first stages of production such as order entry and product design to downstream processes such as parts ordering and machine scheduling enables manufacturers to immediately understand the resource implications of producing a new product or order and to better optimize the organization of production.
Connecting robots and other machines to a central computing server enables manufacturers to extract and aggregate data that can be used to optimize machine performance in real-time or retrospectively, avoiding unplanned machine downtime which can cost manufacturers over $1 million per hour.
Virtual representations of robots and other production machines enable manufacturers to simulate operations and the impact of changes to parameters and programs before they are implemented, enabling improved production planning, and avoiding costly downtime.
Robots as a Service:
Adopting robots on a pay-per-use basis can be particularly beneficial for small-to-medium-sized manufacturers, sparing them up front capital investment and unpredictable maintenance costs, and giving them predictability of operating expenditure.
Sense and Respond:
Sensors and vision systems enable robots to respond to their external environment in real-time, expanding the range of tasks the robot can perform - such as picking and placing unsorted parts - and expanding robot mobility. Mobile robots are key to enabling flexible manufacturing, in which production is split into discrete processes and production cells running in parallel.