Authors: Mehdi Amine Naji; Ahmed Mousrij; Valentina Cillo; Roberto Chierici
Addresses: Mechanical Engineering, Industrial Management and Innovation Laboratory, Faculty of Science and Technology, Hassan 1st University, P.O. Box 577, Settat, Morocco ' Mechanical Engineering, Industrial Management and Innovation Laboratory, Faculty of Science and Technology, Hassan 1st University, P.O. Box 577, Settat, Morocco ' Department of Management, Università Politecnica delle Marche, Piazzale Martelli 8, 60121 Ancona, Italy ' Department of Business and Law, University of Milano – Bicocca, Via Bicocca degli Arcimboldi, 8, 20126 Milano, Italy
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.
Keywords: maintenance performance measurement; maintenance performance indicator; fuzzy set; multi-criteria decision-making; MCDM; analytical hierarchy process; AHP.
International Journal of Managerial and Financial Accounting, 2019 Vol.11 No.3/4, pp.290 - 319
Received: 07 Feb 2019
Accepted: 07 Sep 2019
Published online: 04 Dec 2019 *