Optimal maintenance strategy selection based on a fuzzy analytical network process: A case study on a 5-MW powerhouse

Abstract

Maintenance is one of the most crucial issues in today’s competitive manufacturing environment. Nowadays, productive methods are used in manufacturing plants to improve operations capabilities, which alternatively change business environmental factors leading to a competitive market. Consequently, selection and illustration of an optimal maintenance strategy play a significant role in achieving these goals. Also, lack of an integrated model is felt, one that consists of available criteria and options, a systematic approach in setting maintenance instructions and robust maintenance decision-making. So, based on the fuzzy analytical network process (FANP) method, which composes criteria and options, a new approach to selecting optimal maintenance strategy is proposed in this article. Here, using multi-attribute decision-making in conjunction with application of fuzzy numbers structure has been regarded as an efficacious method for determining the significance of each criterion and option. The criteria that are considered in the FANP method are organization, safety, administration, staff, and technical requirements. The options (strategies) that are taken into consideration in this study are time-based preventive maintenance, corrective maintenance, condition-based maintenance, reliability-centered maintenance, and predictive maintenance. After implementing the method proposed for a 5-MW powerhouse (a case study undertaken for the purpose of this study), the predictive maintenance strategy was selected. According to expert opinions, it is the administrative and staff requirements that must be highlighted for selecting the best strategies.