Evaluating the Performance and Robustness of Condition-Based Maintenance Strategies and Time-Based Maintenance Strategies
Author(s):
Khamiss Cheikh†, EL Mostapha Boudi†*, Rabi Rabi‡, H. Mokhliss‡†
Affiliation(s):
† Department of Mechanical Engineering, Energetic team,Mechanical and Industrial Systems (EMISys),
School Mohammadia of engineer, University Mohammed V, Rabat, Morocco.
‡ Engineering in Chemistry and Physics of Matter Laboratory, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni-Mellal, 23000, Morocco
‡† Department of Physics, Laboratory of Electronics, Instrumentation and Energetics, Faculty of Sciences, Chouaib Doukkali University El Jadida, Morocco.
*Corresponding author: [email protected]
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Numerous studies in the literature have demonstrated that condition-based maintenance strategies are highly effective in achieving maximum system availability while minimizing maintenance expenses. Typically, these strategies’ economic performance is evaluated using a widely recognized criterion known as the “long-term expected maintenance cost rate. However, it’s less common for researchers to examine the robustness of these strategies, considering that maintenance costs can fluctuate significantly from one maintenance cycle to the next. It’s clear that solely evaluating a maintenance strategy based on the cost criterion mentioned above doesn’t guarantee its robustness. This is because it can result in either overestimating or underestimating budgetary requirements. In light of this, the current paper seeks to create a cost model that not only measures economic performance but also evaluates robustness in assessing condition-based maintenance strategies. The study examines two prominent maintenance strategies: one involving periodic inspection and replacement, and the other based on quantiles, determining inspection and replacement intervals. By comparing these strategies, the research aims to identify the key factors that predominantly influence their performance and robustness. This analysis will provide valuable insights for selecting the most suitable maintenance strategy in various scenarios.