Operator 4.0 - A survey
Framework of Operator 4.0 Solutions
The concepts of Operator 4.0, cyber-physical systems and intelligent space are introduced and connections between these methodologies discussed.
The Operator 4.0 studies are based on Prof. Dr David Romero et al., who first defined the Operator 4.0 paradigm. Their project is "The Operator 4.0 - Towards Socially Sustainable Factories of the Future", which is the basics of all of the further researches and applications besides this topic.
The Operator 4.0 Concept* and Human-Cyber-Physical Systems
Operator 4.0 typology depicts how the technologies of the fourth industrial revolution will assist the work of operators . Operator 1.0 is defined as humans conducting manual work. The Operator 2.0 generation represents a human entity whose job is supported by tools, e.g. by computer numerical control (CNC) of machine tools. In the third generation, the humans are involved in cooperative work with robots and computer tools, also known as human-robot collaboration. This human-robot collaboration in the industrial environment is a fascinating field with a specific focus on physical and cognitive interaction. However, the new set of solutions is based on even more intensive cooperation between operators and production systems. This new Operator 4.0 concept represents the future of workplaces.
Analytical Operator-type solutions utilize Big Data Analytics to collect, organize and analyze large data sets Augmented reality (AR) can be considered as a critical enabling technology for improving the transfer of information from the digital to the physical world of the smart operator. The Collaborative Operator works together with collaborative robots (CoBots). Healthy Operator solutions measure and store exercise activity, stress, heart rate and other health-related metrics as well as GPS location and other personal data. Smarter Operators interact with machines, computers, databases and other information systems as well as receive useful information to support their work. Social Operators use mobile and social collaborative methods to connect to smart factory resources. Super-Strength Operators increase the strength of human operators to be able to conduct manual tasks without effort using wearable exoskeletons, while Virtual Operators interact with the computer mapping of design, assembly or manufacturing environments.
Whit regards to the development of Operator 4.0-based automation systems, attention has to be paid to the design principles of Industry 4.0 solutions, which are decentralization, virtualization, reconfiguration and adaptability. How these principles should be applied during the development process is presented in.
The Operator 4.0 concept aims to create Human-Cyber-Physical Production Systems (H-CPPS) that improve the abilities of the operators. The allocation of tasks to machines and operators requires the complex semantic model of the H-CPS. Operator instructions can be programmed into a machine and but handling uncertainty and stochastic nature is difficult. Adaptive systems are suitable to handle these problems with the help of more frequent monitoring and model adaptation functions . Real-time operator support and performance monitoring require accurate information concerning the activities of operators, which means all data related to operator activities should be measured, converted, analyzed, transformed into actionable knowledge and fed back to the operators. Based on this requirement the operator should be connected from the bottom (connection) to the top (configuration) levels of the cyber-physical systems.
As tasks should be transformed into a form that computers can understand, task analysis is becoming more and more crucial due to the difficulties of the externalization of the tacit knowledge the operators Tacit knowledge contains all cognitive skills and technical know-how that is challenging to articulate. Without elicit tacit knowledge, the chance of losing critical information and best practice is very high. Hierarchical task analysis extended with the `skill, rule and knowledge'' framework can capture tacit knowledge, which approach has been proven to be useful in manufacturing.
Sensor technologies are essential to elicit tacit knowledge, for example, the tacit knowledge of the operator can be captured by a 'sensorized' hand-held belt grinder and a 3D scanner to generate a program of a robot that can replace the operator. The modelling of the physical reality and realising it in the CPS are critical tasks.
These examples illustrate that Operator 4.0 solutions should be based on contextual task analysis which requires precise chronological time-synchronization of the operator actions, sensory data and psycho-physiological signals to infer the cognitive states and emotions associated with the decisions and operator actions.
Sensors and feedback technologies of interactive intelligent space can be used not only for improving the abilities of the operators but also for the extraction of their tacit knowledge. In the following section, these technologies will be detailed.
Further information: https://doi.org/10.3390/app8091650.
* Romero, David, et al. "Towards an operator 4.0 typology: a human-centric perspective on the fourth industrial revolution technologies." proceedings of the international conference on computers and industrial engineering (CIE46), Tianjin, China. 2016. - https://bit.ly/3pOi3gm