A new integrated strategy for optimising the maintenance cost of complex systems using reliability importance measures

AbstractWith the aging of production systems, failure modes become more common resulting in additional maintenance costs. To reduce these costs excess, flexible and smart maintenance strategies should be considered. This article proposes an integrated condition-based maintenance method associating opportunistic and importance measure concepts (IMC). The objective of an IMC-based model is to determine the contribution of the system’s components according to their criticality degree for reliability improvement and maintenance planning. The identification of the best maintenance planning consists of determining the expected minimal cost that guarantees the repair actions of a group of critical components in one shot. Therefore, determining IMC values is not so easy for complex systems, it requires knowing their operational structure, the determination of the reliability value of each configuration and finally calculating each component's IMC degree and ranking them for the prioritisation selection. For testing the proposed method, an industrial case study has been used, regarding a complex system whose components fail at random times. The system undergoes minimal repairs if one or more components fail accidentally or by decision after inspection actions. The numerical results show that the developed approach incurs minimal maintenance costs, and can be integrated as a decision-aid solution for manufacturers.KEYWORDS: Basic and opportunistic condition-based maintenanceimportance measure concepts; reliability structure–function; minimal paths & cuts setsmulti-component production systems Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementData sharing is not applicable to this article as the only data used for the purpose of this study have been contained in this article.Additional informationFundingThis work was supported by Natural Sciences and Engineering Research Council of Canada: https://www.nserc-crsng.gc.ca/Notes on contributorsMohamed-Larbi RebaiaiaMohamed-Larbi Rebaiaia holds a doctorate degree (PhD) in Industrial Engineering from Laval University (Canada), a doctorate degree in Computer Science from Batna University, and a Master by Science in Operational Research from Annaba university (Algeria). He is currently a researcher in Production & operations management, and reliability & maintenance engineering, at the Science and Engineering faculty (Laval University), since 2008. Before 2007, he was an assistant professor in Computer Science and Operational Research at Annaba and Batna universities. His research interests include Networks Reliability Evaluation & Optimisation, Maintenance Engineering, Production Management & Planning, and Software Engineering, Machines Learning & AI.Daoud Ait-KadiDaoud Ait-Kadi holds a doctorate degree (PhD) in Industrial Engineering and a master’s degree in applied sciences from Polytechnique school at Montreal University (Canada). He is a Full professor and researcher in the fields of Modelling, Optimisation and Validation of the Reliability, Maintainability and Availability of systems subject to one or more degradation modes, Integrated Logistical Support, Design and Management of value creation networks, Management of end-of-life Products and Reverse Logistics, Management of spare parts, Optimisation of Systems’ Performance with a view to Sustainable Development.