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A Comparison of Multi-Criteria Decision Making Approaches for Maintenance Strategy Selection (A Case Study)
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Author(s): Malek Tajadod (Department of Industrial Engineering, Shahid Bahonar University, Kerman, Iran), Mohammadali Abedini (Department of Industrial Engineering, Iran University of Science and Technology (IUST), Tehran, Iran), Ali Rategari (School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna, Sweden & Volvo GTO, Köping, Sweden)and Mohammadsadegh Mobin (Department of Industrial Engineering and Engineering Management, Western New England University, Springfield, MA, USA)
Copyright: 2016
Volume: 7
Issue: 3
Pages: 19
Source title:
International Journal of Strategic Decision Sciences (IJSDS)
Editor(s)-in-Chief: Saeed Tabar (Ball State University, USA)
DOI: 10.4018/IJSDS.2016070103
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Abstract
The growth of world-class manufacturing companies and global competition caused significant changes in the manufacturing companies operations. These changes have affected maintenance and made its role even more crucial to stay ahead of the competition. Maintenance strategy selection is one of the strategic decision-making issues that manufacturing companies in the current competitive world are facing. In this paper, a comparison between different Multiple Criteria Decision Making (MCDM) approaches is conducted in a dairy manufacturing factory to rank the maintenance strategies. The aim is to suggest an appropriate approach for the best selection of the maintenance strategy. The decision-making elements including evaluation criteria/sub-criteria and problem alternatives, i.e., maintenance strategies are determined and a group of experts from the case-study factory are asked to make their pair-wise comparisons. The pair-wise comparison matrix is constructed by using the crisp and triangular fuzzy numbers, while the aggregation of individual priorities (AIP) approach is utilized to aggregate the decision-makers' judgments. The priority vectors of decision elements are calculated by Mikhailov's fuzzy preference programming (FPP) methods and the final weights of the decision elements are found. Results show that when the effectiveness of one element on the other elements is higher, it will have greater weights; and therefore, the results from the analytic network process (ANP) method is completely different from those of the analytic hierarchy process (AHP). The reason for the differences between the AHP and Fuzzy AHP (FAHP) with the ANP and Fuzzy ANP (FANP) is that both AHP and FAHP evaluate the criteria only based on the level of importance and do not consider the interdependencies and interactions among the evaluation elements. In this research, a predictive maintenance is selected as the most appropriate strategy in the case company and the preventive strategies outperformed the corrective strategies. The results of this research are consistent with the results of previous studies found in the literature.
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