Contribution à la maintenance prévisionnelle des systèmes de production par la formalisation d'un processus de pronostic

Abstract : Today, due to the emergence of sustainability constraint within Enterprise, the industrial people have to integrate in the development strategy, not only the conventional economical finality but also the social and environmental requirements. At the Manufacturing Execution System (MES) level, this objective is materialised through the concept of System Maintaining in Operational Conditions (SMOC). In order to improve the SMOC efficiency, this thesis outlines the formalisation of the key Predictive Maintenance process which is the prognosis one. The deployment of the prognosis process follows a methodology based both of probabilistic and event approaches. The probabilistic model which supports the prognosis execution, has been developed by means of Dynamic Bayesian Networks (DBN). The feasibility and added value of this new prognosis is experimented on the manufacturing TELMA platform supporting the unwinding of metal bobbin.
Document type :
Theses
Complete list of metadatas

Cited literature [211 references]  Display  Hide  Download

https://hal.univ-lorraine.fr/tel-01748086
Contributor : Thèses Ul <>
Submitted on : Thursday, March 29, 2018 - 11:24:14 AM
Last modification on : Thursday, April 12, 2018 - 1:57:47 AM
Long-term archiving on : Friday, September 14, 2018 - 12:20:41 AM

File

SCD_T_2005_0015_MULLER.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : tel-01748086, version 1

Collections

Citation

Alexandre Muller. Contribution à la maintenance prévisionnelle des systèmes de production par la formalisation d'un processus de pronostic. Autre [cs.OH]. Université Henri Poincaré - Nancy 1, 2005. Français. ⟨NNT : 2005NAN10015⟩. ⟨tel-01748086⟩

Share

Metrics

Record views

40

Files downloads

37