A fuzzy-grey-weighted aggregate sum product assessment methodical approach for multi-criteria analysis of maintenance performance systems

Abstract

Diverse maintenance performance models have been previously proposed in literature. However, many of these frameworks perform inefficiently or are not applicable in real-world problems due to their over-simplified assumptions. Such models do not take into account peculiarities of the maintenance situation in which multiple factors need to be prioritised under uncertain conditions. Keeping the above issues in mind, this communication proposes a framework for ranking maintenance performance systems using integrated fuzzy entropy weighting method, grey relational analysis (GRA) and weighted aggregate sum product assessment (WASPAS). The values of criteria weights were determined using fuzz entropy weighting method. Ranking was carried out using GRA and WASPAS methods. GRA ranking considered a criterion, while WASPAS method considered multi-criteria. It is the belief of the authors that merging these three mentioned tools generates synergy. The synergic advantage of the fusion is that these tools interact to create the combined results of ability to handle logic decisions, or partial information and choice among complex alternatives, demonstrated in this paper. The built-up frame-work was illustrated with practical data from five manufacturing companies operating in Nigeria with information gathered through the questionnaire approach to show that the approach can be effectively implemented in practice. Based on the proposed framework’s results, the highest ranked maintenance system belongs to companies 4 and 5, while the lowest ranked maintenance system belongs to company 5. TOPSIS method was used to determine the best performing maintenance function of the companies. It was observed that maintenance system of company 4 was the highest ranked system. The results from model testing confirmed that the presented scheme is feasibility in industrial settings, efficient and capable of revealing the best company in performance according to certain six input criteria. The novelty of this approach is its uniqueness of the combined frameworks’ structures in achieving the highest accuracy of estimation, introduced for the first time in maintenance performance assessment in a multi-criteria framework.