Modèles de processus de collecte de données et d'évaluation de performance de disponibilité pour l'aide à la décision en maintenance

Abstract : This thesis proposes a modeling approach of an adaptive and iterative data collection process, and a validation tool via operational effectiveness features for equipment. An approach, named "Tropos", established based on the information theory, is developed to modeling and evaluating data collection processes. This is an original approach, which allows synthesizing three features that characterize the effectiveness of a data collection process: 1) data usefulness, 2) process complexity, 3) gain of information by a basic process activity. An original model, based on colored stochastic Petri nets coupled to the Monte Carlo simulation, has also been developed to validate the effectiveness of the data collection process. This model uses as input, stochastic process models of degradation, of failure and of maintenance of equipment components. The input parameters of the models are assumed to be known and obtained from the collected data. The properties of colored stochastic Petri net model are also used to derive the minimum cuts required to assess the equipment condition and operational effectiveness. These properties also allow to treating systems of k/n structures. The effectiveness of the proposed approach is finally illustrated on a multi-source renewable energy production system, by implementing the algorithms of the model under the Silab software environment
Complete list of metadatas

Cited literature [146 references]  Display  Hide  Download

https://hal.univ-lorraine.fr/tel-01750638
Contributor : Thèses Ul <>
Submitted on : Thursday, March 29, 2018 - 12:51:09 PM
Last modification on : Friday, May 17, 2019 - 11:37:43 AM

File

DDOC_T_2013_0287_WANG.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : tel-01750638, version 1

Citation

Zhouhang Wang. Modèles de processus de collecte de données et d'évaluation de performance de disponibilité pour l'aide à la décision en maintenance. Autre. Université de Lorraine, 2013. Français. ⟨NNT : 2013LORR0287⟩. ⟨tel-01750638⟩

Share

Metrics

Record views

71

Files downloads

1364