L. Bautista Bárcena, I. Torres Castro, C. Bérenguer, O. Gaudoin, L. Doyen
Industrial systems usually present interrelated parts that influence the system performance. For instance, lighting systems composed of many LED lamps, which show a likely dependence because of their common usage. Maintenance actions are performed on these systems to mitigate the degradation effects and widen their lifetime. In this work, imperfect maintenance actions are implemented by using the so-called ARD (Arithmetic Reduction of Degradation) model. Within this framework, the inference problem in a two-component degrading system is analysed. When parameters are estimated from a degradation model, they usually are obtained from degradation or failure observations. The novelty here is that model parameters are estimated from maintenance information. Different observation strategies are considered, so that degradation levels can be observed between maintenance actions, as well as just before or just after maintenance times.
Keywords: Imperfect maintenance, Statistical inference, Wiener process
Scheduled
Stochastic processes and their applications II
June 12, 2025 3:30 PM
Auditorio 2. Leandre Cristòfol