Applying Predictive Maintenance in Flexible Manufacturing - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2020

Applying Predictive Maintenance in Flexible Manufacturing

Go Muan Sang
  • Fonction : Auteur
  • PersonId : 1025636
Lai Xu
  • Fonction : Auteur
  • PersonId : 992712
Paul De Vrieze
  • Fonction : Auteur
  • PersonId : 1154249
Yuewei Bai
  • Fonction : Auteur
  • PersonId : 1051277

Résumé

In Industry 4.0 context, manufacturing related processes e.g. design processes, maintenance processes are collaboratively processed across different factories and enterprises. The state i.e. operation, failures of production equipment tools could easily impact on the collaboration and related processes. This complex collaboration requires a flexible and extensible system architecture and platform, to support dynamic collaborations with advanced capabilities such as big data analytics for maintenance. As such, this paper looks at how to support data-driven and flexible predictive maintenance in collaboration using FIWARE? Especially, applying big data analytics and data-driven approach for effective maintenance schedule plan, employing FIWARE Framework, which leads to support collaboration among different organizations modularizing of different related functions and security requirements.
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Dates et versions

hal-03745796 , version 1 (04-08-2022)

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Go Muan Sang, Lai Xu, Paul De Vrieze, Yuewei Bai. Applying Predictive Maintenance in Flexible Manufacturing. 21th Working Conference on Virtual Enterprises (PRO-VE), Nov 2020, Valencia, Spain. pp.203-212, ⟨10.1007/978-3-030-62412-5_17⟩. ⟨hal-03745796⟩
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