Affinity analysis using a priori algorithm to identify failure dependence in multi-component systems - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2021

Affinity analysis using a priori algorithm to identify failure dependence in multi-component systems

Résumé

Maintenance decisions in multi-component systems are of great interest to maintenance managers. The equipment during its operation, produces and stores a large amount of data, especially discrete event data such as alarm, failed situation, change of operation modes, stop of the systems, and so forth, and produced via processings supported by PLCs, supervision system, SCADA.. Considering this data to assist in maintenance management and decisions is an area with a growing interest in maintenance management. In this paper, we study the stochastic dependency in a multi-component system through data from CLP database. We use appriory algorithm and affinity function to identify failure dependence in multi-component systems. The results of failure dependence can be used as input for planning group maintenance, purchase spare parts, or planning opportunistic maintenance.

Dates et versions

hal-03379931 , version 1 (15-10-2021)

Identifiants

Citer

Rodrigo Lopez, Phuc Do Van, Cristiano Cavalcante, Benoît Iung. Affinity analysis using a priori algorithm to identify failure dependence in multi-component systems. 11th IMA International Conference on Modelling in Industrial Maintenance and Reliability, MIMAR 2021, Jun 2021, Virtual conference, United Kingdom. ⟨10.19124/ima.2021.01.4⟩. ⟨hal-03379931⟩
31 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More