A Framework for Manufacturing System Reconfiguration based on Artificial Intelligence and Digital Twin

Mo, Fan; Chaplin, Jack C.; Sanderson, David; Rehman, Hamood Ur; Monetti, Fabio Marco; Maffei, Antonio; Ratchev, Svetan

Abstract

The application of digital twins and artificial intelligence to manufacturing has shown potential in improving system resilience, responsiveness, and productivity. Traditional digital twin approaches are generally applied to single, static systems to enhance a specific process. This paper proposes a framework that applies digital twins and artificial intelligence to manufacturing system reconfiguration, i.e., the layout, process parameters, and operation time of multiple assets, to enable system decision making based on varying demands from the customer or market. A digital twin environment has been developed to simulate the manufacturing process with multiple industrial robots performing various tasks. A data pipeline is built in the digital twin with an API (application programming interface) to enable the integration of artificial intelligence. Artificial intelligence methods are used to optimise the digital twin environment and improve system decision-making. Finally, a multi-agent program approach shows the communication and negotiation status between different agents to determine the optimal configuration for a manufacturing system to solve varying problems. Compared with previous research, this framework combines distributed intelligence, artificial intelligence for decision making, and production line optimisation that can be widely applied in modern reactive manufacturing applications.

Citation

Mo, F., Chaplin, J. C., Sanderson, D., Rehman, H. U., Monetti, F. M., Maffei, A., & Ratchev, S. (2022). A Framework for Manufacturing System Reconfiguration based on Artificial Intelligence and Digital Twin. In Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus Proceedings of FAIM 2022, June 19-23, 2022, Detroit, Michigan, USA, Volume 2 (361-373). https://doi.org/10.1007/978-3-031-18326-3_35

• Conference Name: Flexible Automation and Intelligent Manufacturing International Conference (FAIM 2022)
• Conference Location: Detroit, USA
• Start Date: Jun 19, 2022
• End Date: Jun 23, 2022
• Acceptance Date: May 5, 2022
• Online Publication Date: Oct 13, 2022
• Publication Date: Oct 13, 2022
• Deposit Date: May 16, 2022
• Publicly Available Date: Oct 14, 2023
• Publisher: Springer
• Pages: 361-373
• Series Title: Lecture Notes in Mechanical Engineering
• Series ISSN: 2195-4356
• Book Title: Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus Proceedings of FAIM 2022, June 19-23, 2022, Detroit, Michigan, USA, Volume 2
• ISBN: 9783031183256
• DOI: https://doi.org/10.1007/978-3-031-18326-3_35
• Public URL: https://nottingham-repository.worktribe.com/output/8129288
• Publisher URL: https://link.springer.com/chapter/10.1007/978-3-031-18326-3_35
• Additional Information: First Online: 13 October 2022; Conference Acronym: FAIM; Conference Name: International Conference on Flexible Automation and Intelligent Manufacturing; Conference City: Detroit, MI; Conference Country: USA; Conference Year: 2022; Conference Start Date: 19 June 2022; Conference End Date: 23 June 2022; Conference ID: faim2022; Conference URL: https://www.faimconference.org/