Abstract
Human workers are envisioned to work alongside robots and other intelligent factory modules, and fulfill supervision tasks in future smart factories. Technological developments, during the last few years, in the field of smart factory automation have introduced the concept of cyber-physical systems, which further expanded to cyber-physical production systems. In this context, the role of collaborative robots is significant and depends largely on the advanced capabilities of collision detection, impedance control, and learning new tasks based on artificial intelligence. The system components, collaborative robots, and humans need to communicate for collective decision-making. This requires processing of shared information keeping in consideration the available knowledge, reasoning, and flexible systems that are resilient to the real-time dynamic changes on the industry floor as well as within the communication and computer network infrastructure. This article presents an ontology-based approach to solve industrial scenarios for safety applications in cyber-physical production systems. A case study of an industrial scenario is presented to validate the approach in which visual cues are used to detect and react to dynamic changes in real time. Multiple scenarios are tested for simultaneous detection and prioritization to enhance the learning surface of the intelligent production system with the goal to automate safety-based decisions.
Highlights
The current era is experiencing the revolution of the production systems, using interconnected equipment, automation of processes, real-time data processing for developing decision tools, and human–machine collaboration
Internet of things (IoT) is an emerging communication protocol through which the elements of cyber-physical production systems (CPPSs) can interact with each other having unique identity.[4]. This further leads to the concept of production systems which are autonomous through the use of artificial intelligence (AI) and IoT commonly known as smart factories.[5]
The complex real-world industrial scenario comprises a large number of elements that interact in a non-linear way with each other and exhibit the emergence of unplanned activities, lack of complete knowledge, and ethical and safety issues. This is a new domain in which the conventional visual cues method and ontology-based modeling are implemented with AI to manage industrial operations in an intelligent way that can provide a thinking base to the CPPS
Summary
The current era is experiencing the revolution of the production systems, using interconnected equipment, automation of processes, real-time data processing for developing decision tools, and human–machine collaboration. The CPS can be termed as a smart system incorporating physical and computational elements.[1] These elements can be distributed into four portions, that is, sensing, networking, analysis, and application.[2] In the realm of Industry 4.0, a new term of cyber-physical production systems (CPPSs) emerged in Germany that proposed complete automation of production systems, incorporating interconnected physical elements such as robots, conveyors, sensors, and actuators controlled by computational elements These systems are flexible to the extent that they incorporate changes which are already stated or provided through decision rules.[3] Internet of things (IoT) is an emerging communication protocol through which the elements of CPPS can interact with each other having unique identity.[4] This further leads to the concept of production systems which are autonomous through the use of artificial intelligence (AI) and IoT commonly known as smart factories.[5] the robots and computers take a major share in the CPS, human presence is essential for productivity either for supervision or for complicated jobs that robots cannot undertake. This can be done by increasing flexibility in the system to encounter any contingency in the task, for example, finding a bolt while performing an operation on a nut, in an assembly line
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
