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Autonomic computing in manufacturing process coordination in industry 4.0 context

Abstract : Industry 4.0 is defined as a paradigm that integrates the latest technological inventions in Artificial Intelligence (AI), Communication, and Information technologies, among other domains. This integration is made to increase the levels of automation, efficiency, and productivity of production, in manufacturing and industrial processes. In particular, the actors of the production processes (Things, Data, People and Services) should autonomously be able to act and make decisions, to implement self-* properties, such as self-configuration, self-management, and self-healing. In that sense, the Industry 4.0 revolution introduces many new challenges and issues that need to be solved. Some of those challenges are related to the integration of the heterogeneous actors that carry out the manufacturing process's tasks. Moreover, it is crucial to determine how to permit the actors to self-manage the production processes. In this paper, we present a framework for the integration of autonomous processes based on the needs for coordination, cooperation, and collaboration. Notably, we define three autonomic cycles that allow the actors of manufacturing processes (Data, People, Things, and Services) to interoperate. These autonomic cycles can create a coordinated plan for self-configuration, self-optimization, and self-healing during the manufacturing process. In this way, the actors can be appropriately coordinated, oriented to autonomously manufacture Smart Products, detect failures, and recover from errors or failures, among other things.
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https://hal-cnrs.archives-ouvertes.fr/hal-02956703
Contributor : Manuel Sanchez <>
Submitted on : Saturday, October 3, 2020 - 12:48:57 PM
Last modification on : Wednesday, October 14, 2020 - 4:12:17 AM

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Manuel Sanchez, Ernesto Expósito, Jose Aguilar. Autonomic computing in manufacturing process coordination in industry 4.0 context. Journal of Industrial Information Integration, Elsevier, 2020, 19, pp.1-16. ⟨10.1016/j.jii.2020.100159⟩. ⟨hal-02956703⟩

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