An integrated data- and capability-driven approach to the reconfiguration of agent-based production systems

Industry 4.0 promotes highly automated mechanisms for setting up and operating flexible manufacturing systems, using distributed control and data-driven machine intelligence. This paper presents an approach to reconfiguring distributed production systems based on complex product requirements, combining the capabilities of the available production resources. A method for both checking the “realisability” of a product by matching required operations and capabilities, and adapting resources is introduced. The reconfiguration is handled by a multi-agent system, which reflects the distributed nature of the production system and provides an intelligent interface to the user. This is all integrated with a self-adaptation technique for learning how to improve the performance of the production system as part of a reconfiguration. This technique is based on a machine learning algorithm that generalises from past experience on adjustments. The mechanisms of the proposed approach have been evaluated on a distributed robotic manufacturing system, demonstrating their efficacy. Nevertheless, the approach is general and it can be applied to other scenarios.

URI

http://hdl.handle.net/10454/19287

Version

Published version

Citation

Scrimieri D, Adalat O, Afazov S et al (2022) An integrated data- and capability-driven approach to the reconfiguration of agent-based production systems. International Journal of Advanced Manufacturing Technology. 124: 115-1168.

Link to Version of Record

https://doi.org/10.1007/s00170-022-10553-0

Type

Article

Notes

Research Development Fund Publication Prize Award winner, Nov 2022