Implementing self-* autonomic properties in self-coordinated manufacturing processes for the Industry 4.0 context

Mise en œuvre de propriétés autonomes dans des processus de fabrication auto-coordonnés pour l'industrie 4.0

Manuel Sanchez (1, 2, 3, 4) , E. Exposito (1) , J. Aguilar (2, 5, 4)

1 LIUPPA - Laboratoire Informatique de l'Université de Pau et des Pays de l'Adour
2 ULA - Universidad de Los Andes [Mérida, Venezuela]
3 Universidad Nacional Experimental del Táchira
4 Tepuy R+D - Tepuy R+D Group, Artificial Intelligence Software Development
5 EAFIT - EAFIT University

Industry 4.0 requires high levels of autonomy in order to guarantee the manufacturing processes to achieve production goals. For this, it is needed high levels of coordination, cooperation, and collaboration, such that the manufacturing process’ actors can communicate and interoperate. A previous paper proposed three autonomic cycles of data analytics tasks for self-coordination in manufacturing processes. In this paper, we implement one of these autonomic cycles, allowing self-supervising of the coordination process. This autonomic cycle is designed using the MIDANO’s methodology, and implemented and tested using an experimental tool that was developed to replay the production process event logs, in order to detect failures and invoke the autonomic cycle for self-healing when needed.

Mots clés: Industry 4.0; Self-supervising; Autonomic computing; Process mining; Self-coordination

Domaines: Intelligence artificielle [cs.AI]; Ingénierie assistée par ordinateur; Apprentissage [cs.LG]

Manuel Sanchez, E. Exposito, J. Aguilar. Implementing self-* autonomic properties in self-coordinated manufacturing processes for the Industry 4.0 context. Computers in Industry, 2020, 121, pp.103247. ⟨10.1016/j.compind.2020.103247⟩. ⟨hal-02956700⟩