Supervision : Jacques MALENFANT

Co-supervision : DHOUIB Saadia

Digital twin for the dynamic orchestration of autonomous and embedded systems

As control and information technology advance, modern manufacturing systems are evolving towards increased automation and intelligence. The concept of the digital twin is becoming increasingly prominent across various sectors, offering a clear method for managing complex systems via digital counterparts. However, this emerging field presents several critical challenges and research questions, particularly in applying digital twin systems to industry. Beyond the established challenges in supervising complex cyber-physical systems, there is a pressing need for a comprehensive, interoperable representation of products, production processes, and plant resources that can integrate seamlessly with diverse equipment. This thesis investigates three primary issues: interoperability, adaptability, and robustness of manufacturing systems in the context of Industry 4.0. A capability-based self-adaptive manufacturing architecture (CBSAM) has been proposed in this thesis, utilizing software engineering approaches like capability-based engineering, Model-Driven Engineering (MDE), and the MAPE-K (Monitor, Analyze, Plan, Execute, and Knowledge) framework to enhance the adaptability and efficiency of production systems.
The proposed architecture incorporates a feedback loop to enable the self-adaptivity of the digital twin system, which ensures the continuity of the production process on its performance and adapts to changes in the physical system. This research extends beyond conceptual methods to develop practical software tools, integrating Digital Twin (DT) technology into an existing Model-Based Systems Engineering (MBSE) ecosystem to complete the CBSAM architecture. An academic testbed developed in the laboratory showcases the CBSAM methodology’s implementation in detail. Finally, this thesis concludes with a generalization to the architecture and the completion of the implementation as a perspective for the future.

2021-2024 Publications

• 2024
  • Y. Huang : “Digital twin for the dynamic orchestration of autonomous and embedded systems”, thesis, phd defence 02/08/2024, supervision Malenfant, Jacques, co-supervision : Dhouib, Saadia (2024)
• 2023
  • Y. Huang, S. Dhouib, L. Palacios Medinacelli, J. Malenfant : “Semantic Interoperability of Digital Twins: Ontology-based Capability Checking in AAS Modeling Framework”, 2023 IEEE 6^th International Conference on Industrial Cyber-Physical Systems (ICPS), Wuhan, China, pp. 1-8, (IEEE) (2023)
• 2022
  • Y. Huang, S. Douib, L. Palacios Medinacelli, J. Malenfant : “Enabling Semantic Interoperability of Asset Administration Shells Through an Ontology-based Modeling Method”, MODELS '22: Proceedings of the 25^th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings, Montréal, Canada, pp. 497-502, (Association for Computing Machinery), (ISBN: 9781450394673) (2022)
• 2021
  • Y. Huang, S. Dhouib, J. Malenfant : “An AAS Modeling Tool for Capability-Based Engineering of Flexible Production Lines”, IECON 2021 - 47^th Annual Conference of the IEEE Industrial Electronics Society, Toronto, Canada, pp. 1-6, (IEEE) (2021)
  • Y. Huang, S. Dhouib, J. Malenfant : “AAS Capability-Based Operation and Engineering of Flexible Production Lines”, 2021 26^th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Vasteras, Sweden, pp. 01-04, (IEEE) (2021)