Condition-based Maintenance Optimization of Degradable Systems

Author:

Wei Shuaichong1,Nourelfath Mustapha1,Nahas Nabil2

Affiliation:

1. Mechanical Engineering Department, Laval University, Quebec, Canada.

2. Département d’Administration, Université de Moncton, Moncton (NB), Canada.

Abstract

This paper develops a mathematical model for condition-based maintenance optimization of multi-state systems. The majority of the existing literature on maintenance optimization assume that there is no additional cost incurred because of side effects of equipment degradation. Nevertheless, as the operating cost increases with equipment age and degradation, it is important to consider the degradation side effects in the maintenance decision-making process. An important feature of the proposed model lies in the fact that it incorporates side effect of degradation process into condition-based preventive maintenance optimization. We develop a continuous-time discrete-state Markov chain model describing the deterioration stochastic process of a single component. The component is modeled as a multi-state system, where each discrete state is characterized by a degradation level. Numerical examples show the importance of considering such side effect costs when optimizing the choice of maintenance policy. The proposed model is extended to deal with multi-state series systems. Using an example of a series system with two components, it is shown that preventive maintenance and side effect costs should not be optimized for each component individually, but from the perspective of the series system as a whole.

Publisher

International Journal of Mathematical, Engineering and Management Sciences plus Mangey Ram

Subject

General Engineering,General Business, Management and Accounting,General Mathematics,General Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fault Analysis and Preventive Maintenance of Rocket Vertical Assembly and Test Plant System;International Journal of Mathematical, Engineering and Management Sciences;2023-12-01

2. Reliability Evaluation and Prediction Method with Small Samples;International Journal of Mathematical, Engineering and Management Sciences;2023-08-01

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