### International Journal of Mathematical, Engineering and Management Sciences

#### ISSN: 2455-7749 . Open Access

Condition-based Maintenance Optimization of Degradable Systems

#### Condition-based Maintenance Optimization of Degradable Systems

Shuaichong Wei
Mechanical Engineering Department, Laval University, Quebec, Canada.

Mustapha Nourelfath
Mechanical Engineering Department, Laval University, Quebec, Canada.

Nabil Nahas

;
Accepted on December 17, 2021

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.

Keywords- Maintenance, Degradation side effects, Multi-state systems, Markov chains, Optimization

Citation

Wei, S., Nourelfath, M., & Nahas, N. (2022). Condition-based Maintenance Optimization of Degradable Systems. International Journal of Mathematical, Engineering and Management Sciences, 7(1), 1-15. https://doi.org/10.33889/IJMEMS.2022.7.1.001.