PERTANIKA JOURNAL OF SOCIAL SCIENCES AND HUMANITIES

 

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ISSN 0128-7702

Home / Regular Issue / JSSH Vol. 30 (2) Apr. 2022 / JST-2813-2021

 

Maintenance Strategy Selection using Fuzzy Delphi Method in Royal Malaysian Air Force

Shahizan Ahmad, Norhafezah Kasmuri, Nor Asyikin Ismail, Mohd Fuad Miskon and Nor Hanuni Ramli

Pertanika Journal of Social Science and Humanities, Volume 30, Issue 2, April 2022

DOI: https://doi.org/10.47836/pjst.30.2.02

Keywords: Condition-based maintenance (CBM), fuzzy Delphi method (FDM), preventive maintenance (PM), reactive maintenance (RM)

Published on: 1 April 2022

The proper maintenance strategy is significant in extending assets and equipment, thus saving maintenance within an organization. Currently, there are three types of maintenance strategies implemented in the Royal Malaysian Air Force (RMAF), namely Reactive Maintenance (RM), Preventive Maintenance (PM), and Condition Based Maintenance (CBM). Due to the constraints in terms of maintenance costs by RMAF, choosing the right maintenance strategy is important to ensure that the maintenance provision can be optimized. In this research study, the Fuzzy Delphi Method has been used as a tool in determining the most effective maintenance strategies to be adopted by the RMAF. The output of agreement and opinion from experts in the related field has been used to select the appropriate maintenance strategy. In choosing this maintenance strategy, goals are set first in line with RMAF maintenance’s objectives. The specified maintenance goals are as follows; low maintenance cost, reducing the chance of a breakdown, safety, feasibility on the acceptance by labor, and response time starting from failure. Later, the result showed that the fuzzy score for RM, PM, and CBM was 0.747, 0.789, and 0.767, respectively. The highest fuzzy score showed the most accepted method chosen by the expert. Based on the result and maintenance goals that have been outlined, experts have agreed to choose PM as a maintenance method that should be given priority to be implemented in RMAF compared to other maintenance methods due to the highest fuzzy score.

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