Maintenance Policy Selection Using Fuzzy FMEA and Key Performance Indicators

For decades, maintenance management has been applied in diverse industries to maximize the equipment productivity through maintenance planning, maintenance control, and several improvements regarding to economical features. In maintenance management, Maintenance Policy Selection (MPS) has a key role in determining a proper maintenance strategy based on the real equipment condition. This study is intended to address the concept of Maintenance Policy Selection (MPS) by 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 with different knowledge and experience. The fuzzy approach overcomes the shortcomings of traditional FMEA by considering uncertainty and ambiguity in experts’ point of view. The second step is aimed at evaluation of all criteria that crucially affect Maintenance Policy Selection where four Key Performance Indicators (KPIs) weighted by Fuzzy AHP are defined for equipment criticality assessment. Finally, a new fuzzy approach allocates the most appropriate maintenance strategy to each device based on their criticality and risk values in the third step. In this methodology, internal and external customers’ safety, environmental and economic issues, products quality and equipment reliability and availability are taken into account. A case study of an automotive industry is conducted ii to demonstrate the applicability of the proposed method. The proposed methodology can be applied in different industries for selecting the best maintenance strategies. Keywords: Maintenance policy selection, Failure Mode and Effects Analysis, Analytic Hierarchy Process, Fuzzy Approach

Name thesis:degree_name

Master of Applied Science (MASc)

Level thesis:degree_level

Master's

Discipline thesis:degree_discipline

Engineering - Industrial Systems

Grantor dc:publisher

Faculty of Graduate Studies and Research, University of Regina

Year dc:date.issued

2016

Author dc:creator

• Farajiparvar, Nasrin

Advisor dc:contributor.advisor

• Mayorga, Rene

Committee members dc:contributor.committeemember

• Henni, Amr
• Ismail, Mohamed

Language dc:language.iso

en

DOI

https://doi.org/10.82465/3773

OAI identifier oai:identifier

oai:uregina.scholaris.ca:10294/6823