Abstract
In most industries, such as aerospace, manufacturing, transport and energy sectors, maintenance plays a vital role in improving the performance of safety critical equipment and facilities. It also helps industries achieve the largest possible efficiency, ensure workplace and environmental safety, and reduce unnecessary breakdowns and costs. Therefore, it is crucial for industries to adopt an optimal maintenance strategy for their critical systems and infrastructure. In this study, we aim to propose a novel analytical multi-criteria decision-making (MCDM) methodology for selecting the most suitable maintenance strategy in distillation units of oil refinery plants. The alternative maintenance strategies include run-to-failure (RTF), preventive maintenance (PM), condition-based maintenance (CBM), and reliability centered maintenance (RCM), which are evaluated with respect to 12 sub-criteria in three categories of economical, safety, and sustainability issues. The MCDM methodology consists of a DEMATEL-based analytic network process (ANP) method to determine the importance weights of decision criteria and a VIKOR method to rank the maintenance strategies. Also, interval type-2 fuzzy sets are used to capture uncertainty in experts’ individual judgments. Finally, a real case study is provided to show the applicability of the proposed methodology to an oil refinery plant. The results show that, thanks to advances in degradation modeling, sensor technology, and data analytics platforms, the RCM and CBM are the superior maintenance strategy for crude oil distillation systems.
Highlights
Over the past decades, industrial maintenance has evolved from a set of tasks executed by operators to maintain equipment into a more strategic management issue.[1]
The results showed that preventive maintenance (PM) and predictive maintenance (PdM) were the most suitable strategies for safety critical machines, whereas CM was found to be a proper strategy for non-critical components in the plant
This study proposed a comparative analysis between analytic hierarchy process (AHP), analytic network process (ANP), fuzzy AHP, and fuzzy ANP techniques for selecting the most suitable maintenance strategy in a dairy manufacturing factory
Summary
Industrial maintenance has evolved from a set of tasks executed by operators to maintain equipment into a more strategic management issue.[1]. The development of a maintenance strategy can help businesses provide a plan of action containing specific recommendations on how to maintain their assets in a safe and serviceable condition The implementation of this plan can result in a significant increase in the availability of assets, workplace safety, and environmental integrity. Determining an optimal maintenance management strategy is one of the most important decision-making processes in industrial organizations.[5] Choosing the most suitable maintenance strategy among a set of available options for a piece of equipment involves numerous evaluation criteria, such as cost, safety, time, added-value, reliability, etc. This paper provides a real case study of determining the best maintenance strategy in a crude oil distillation unit
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