Measuring the maintenance performance through fuzzy logic and analytical hierarchy process

Abstract

The paper presents an innovative maintenance performance measurement system that organisations can adopt to identify those predictors that better contribute to achieve higher maintenance standards. Adopting a multi-level, multi-criteria decomposition technique designed to identify and classify key indicators, the study aims to support firms in their decision-making process. Using the fuzzy logic technique, the elementary performance measurement is quantified. Afterwards, by implementing the analytical hierarchy process (AHP) and the weighted arithmetic mean, these measures are aggregated to a holistic measure that quantifies the overall maintenance performance and identifies precisely the requirements to improve continuously and effectively the maintenance performance. Finally, the proposed model was applied to a Moroccan company leader in the chemical sector. The results show that the model effectively allows maintenance managers to properly measure and improve their maintenance performance and support managers in identifying the key actions to enhance their organisations' performance.