TITLE:
Application of Stochastic Optimization to Optimal Preventive Maintenance Problem
AUTHORS:
Petr Volf
KEYWORDS:
Reliability, Preventive Maintenance, MCMC Algorithms, Simulated Annealing, Stochastic Optimization, Accelerated Lifetime Model
JOURNAL NAME:
Journal of Applied Mathematics and Physics,
Vol.9 No.10,
October
14,
2021
ABSTRACT: The contribution deals with the optimization of a sequential preventive maintenance schedule of a technical device. We are given an initial time-to-failure probability distribution, model of changes of this distribution after maintenance actions, as well as the costs of maintenance, of a device acquisition, and of the impact of failure. The maintenance timing and, eventually, its extent, are the matter of optimization. The objective of the contribution is two-fold: first, to formulate a proper (random) objective function evaluating the lifetime of the maintained device relatively to maintenance costs; second, to propose a numerical method searching for a maintenance policy optimizing selected characteristics of this objective function. The method is based on the MCMC random search combined with simulated annealing. It is also shown that such a method is rather universal for different problem specifications. The approach will be illustrated on an artificial example dealing with accelerated lifetime after each maintenance action.