Title: Maintenance policy selection using fuzzy failure modes and effective analysis and key performance indicators

Authors: Nasrin Farajiparvar; Rene V. Mayorga

Addresses: Industrial Systems Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2, Canada ' Industrial Systems Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2, Canada

Abstract: Maintenance policy selection (MPS) plays an important role in determining a proper maintenance strategy based on the real equipment condition. This study is intended to address the concept of MPS proposing an approach to improve current maintenance selection methods. Further, an integrated three-step model is introduced for MPS using fuzzy failure mode and effects analysis (FFMEA) and fuzzy analytical hierarchy process (FAHP). In the first step, a combination of FFMEA and FAHP are applied to calculate the risk of equipment. For the risk priority number computation, three dimensions including severity, occurrence, and detection and their identified sub-dimensions are weighted by three domain experts. The second step is aimed at evaluation of all criteria that crucially affect MPS where four key performance indicators weighted by AHP are defined for equipment criticality assessment. Finally, a novel fuzzy approach is proposed to choose a proper maintenance strategy for each facility according to RPN and criticality scores. A case study is conducted to demonstrate the applicability of the proposed method.

Keywords: maintenance policy selection; failure mode and effects analysis; analytic hierarchy process; fuzzy inference systems.

DOI: 10.1504/IJPQM.2018.094760

International Journal of Productivity and Quality Management, 2018 Vol.25 No.2, pp.170 - 197

Received: 22 Aug 2016
Accepted: 11 Jun 2017
Published online: 15 Sep 2018 *

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