Version 1
: Received: 13 March 2024 / Approved: 14 March 2024 / Online: 14 March 2024 (11:12:17 CET)
How to cite:
Cheikh, K.; Boudi, E.M.; Rabi, R.; Mokhliss, H. Development and Optimization of PIR and QIR Maintenance Strategies Using Monte Carlo Method. Preprints2024, 2024030824. https://doi.org/10.20944/preprints202403.0824.v1
Cheikh, K.; Boudi, E.M.; Rabi, R.; Mokhliss, H. Development and Optimization of PIR and QIR Maintenance Strategies Using Monte Carlo Method. Preprints 2024, 2024030824. https://doi.org/10.20944/preprints202403.0824.v1
Cheikh, K.; Boudi, E.M.; Rabi, R.; Mokhliss, H. Development and Optimization of PIR and QIR Maintenance Strategies Using Monte Carlo Method. Preprints2024, 2024030824. https://doi.org/10.20944/preprints202403.0824.v1
APA Style
Cheikh, K., Boudi, E.M., Rabi, R., & Mokhliss, H. (2024). Development and Optimization of PIR and QIR Maintenance Strategies Using Monte Carlo Method. Preprints. https://doi.org/10.20944/preprints202403.0824.v1
Chicago/Turabian Style
Cheikh, K., Rabi Rabi and Hamza Mokhliss. 2024 "Development and Optimization of PIR and QIR Maintenance Strategies Using Monte Carlo Method" Preprints. https://doi.org/10.20944/preprints202403.0824.v1
Abstract
Every firm is devoted to polishing and fine-tuning its maintenance strategy. More exactly, when we develop robust and efficient preventive and conditional maintenance approaches, our objective is to combine performance and robustness to increase maintenance decision-making. This, in turn, leads to a reduction in system failures and a subsequent drop in related expenses. This impulse drives the origin of this essay: to provide fresh criteria that allow us to improve and optimize maintenance techniques. Furthermore, our study has been realistically utilized via the deployment of condition-based maintenance (CBM) techniques, which are commonly regarded as a critical lever that allows firms to gain a competitive advantage in the context of the fourth industrial revolution.
Combining both perfect and imperfect maintenance actions into CBM strategies appears to be an effective technique to obtain high economic performance and robustness in the maintenance strategies of the companies. Following this idea, we propose and optimize in this paper a set of criteria enabling the combined assessment of the mean economic performance and the resilience of various kinds of maintenance techniques. The advantage of the proposed criterion is that it adapts to different types of maintenance strategies and provides access to a simple and relevant evaluation model. Thanks to this new criterion, we will be able to choose the better maintenance strategies that have more performance and robustness between these strategies for a system with more or less stable behavior. The Monte Carlo Method is incorporated into the comparative assessment of maintenance methods, adding a layer to the evaluation of the performance and robustness of each adaptation in decision-making.
Keywords
Maintenance strategies; decision-making; Condition Based Maintenance strategies; Performance & robustness; system with more or less stable behavior; Monte Carlo Method
Subject
Engineering, Mechanical Engineering
Copyright:
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.
