Evaluating Economic Performance and Robustness of Maintenance Strategies for Degrading Systems

Global competition has driven extraordinary changes in the way firms operate, significantly impacting maintenance functions and emphasizing their critical role in corporate success.To remain competitive, organizations must continuously enhance their maintenance strategies, leading to considerable efforts to improve the economic performance of maintenance for stochastically degrading production systems.This study aims to contribute to robust decision-making in the maintenance of systems vulnerable to gradual deterioration.Our primary objective is to develop criteria that enable the combined assessment of mean economic performance and robustness across various maintenance techniques.The benefit of the suggested criteria is its adaptability to different maintenance strategies, providing a simple yet relevant assessment model.Specifically, this study compares three maintenance strategies: block replacement (BR), periodic inspection and replacement (PIR), and quantile-based inspection and replacement (QIR).These strategies are analyzed using the long-term expected maintenance cost rate as a measure of performance and the variance of maintenance cost per renewal cycle as a measure of robustness.Mathematical cost models are formulated based on the homogeneous Gamma degradation process and probability theory.Using the Monte Carlo method in MATLAB, the study compares these maintenance techniques, applying the proposed criteria to quantify performance and robustness.The study concludes that the developed criteria offer a comprehensive and adaptable framework for evaluating and enhancing maintenance strategies, thereby supporting more effective decision-making in various operational contexts.