Implementation of enterprise operating system (EOS) in industry 4.0 based on the decentralized decision support

Autor: Joseph Rahme Youssef, Gregory Zacharewicz, David Chen, Ricardo Jardim-Goncalves, M. Manuel B. Marques, Carlos Agostinho
Přispěvatelé: Laboratoire de l'intégration, du matériau au système (IMS), Centre National de la Recherche Scientifique (CNRS)-Institut Polytechnique de Bordeaux-Université Sciences et Technologies - Bordeaux 1, Instituto de Desenvolvimento de Novas Tecnologias, FCT Campus, Instituto de Desenvolvimento de Novas Tecnologias [Caparica] (UNINOVA), UNINOVA (UNINOVA), Universidade de Lisboa (ULISBOA), Universidade Nova de Lisboa = NOVA University Lisbon (NOVA)
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC)
2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC), Jun 2017, Funchal, France. ⟨10.1109/ICE.2017.8279998⟩
ICE/ITMC
DOI: 10.1109/ICE.2017.8279998⟩
Popis: Enterprise daily operations are not effectively monitored and controlled. Furthermost of enterprises have chosen to implement ERP solutions or multiple systems in order to facilitate the data orchestration [4]; Nevertheless this solution may constraint the business due to the top down “enclosing” methodology. Considered as an alternative to ERP and a precondition to the future Enterprise 4.0 based on IoT and Cyber physical system principle, this paper tentatively presents a proposal to develop and implement an Enterprise Operating System (EOS) by setting loose coupled connections between enterprise's software with only one simplified central orchestrator component using the Decentralized Decision Support technique. The cooperating parties must accommodate and adjust “on-the-fly” to ensure quick interoperability establishment, easy-pass, and dynamic environment update. In the paper, a set of objectives and functions are identified at first. Then a survey on existing relevant works is presented and mapped to the requirements. After that the role of EOS for Industry 4.0 based on Decentralized Decision Support is described. The architectures of envisioned EOS are outlined and a case study shown to illustrate the use of EOS. The last part draws some conclusions and gives future perspectives.
Databáze: OpenAIRE