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Growing Science » Management Science Letters » Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process

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Management Science Letters

ISSN 1923-9343 (Online) - ISSN 1923-9335 (Print)
Quarterly Publication
Volume 4 Issue 5 pp. 893-898 , 2014

Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process Pages 893-898 Right click to download the paper Download PDF

Authors: Aida Azizi, Kiumars Fathi

DOI: 10.5267/j.msl.2014.3.028

Keywords: Fuzzy AHP, Maintenance, Ranking

Abstract: This paper presents an empirical investigation to rank different factors influencing on maintenance strategies on Iranian oil terminals’ company. The study determines four main factors, production quality, reliability, cost and safety. Using fuzzy analytical process, the study determines various factors associated with each main factor and ranks them by performing pair-wise comparisons. The results indicate that reliability ranks first (0.255), followed by production quality (0.252), cost (0.25) and safety (0.244). In terms of reliability, the best utilization of resources is number one priority followed by increase access to maintenance tools, reduction in production interruption are among the most important issues. In terms of production quality, reduction in system failure as well as reworks is the most important factors followed by customer satisfaction and defects. In terms of cost items, ease of access to accessories and consulting are important factors followed by necessary software, hardware and training programs. Finally, in terms of safety factors, external, internal and employee services are the most important issues, which are needed to be considered.

How to cite this paper
Azizi, A & Fathi, K. (2014). Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process.Management Science Letters , 4(5), 893-898.

Refrences
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Al-Najjar, B. (2007). The lack of maintenance and not maintenance which costs: a model to describe and quantify the impact of vibration-based maintenance on company & apos; s business. International Journal of Production Economics, 107(1), 260-273.

Arunraj, N. S., & Maiti, J. (2007). Risk-based maintenance—techniques and applications. Journal of Hazardous Materials, 142(3), 653-661.

Arunraj, N. S., & Maiti, J. (2010). Risk-based maintenance policy selection using AHP and goal programming. Safety science, 48(2), 238-247.

Bertolini, M., & Bevilacqua, M. (2006). A combined goal programming—AHP approach to maintenance selection problem. Reliability Engineering & System Safety, 91(7), 839-848.

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Cheung, A., Ip, W. H., & Lu, D. (2005). Expert system for aircraft maintenance services industry. Journal of Quality in Maintenance Engineering, 11(4), 348-358.

Eti, M. C., Ogaji, S. O. T., & Probert, S. D. (2006). Development and implementation of preventive-maintenance practices in Nigerian industries. Applied Energy, 83(10), 1163-1179.

Mon, D. L., Cheng, C. H., & Lin, J. C. (1994). Evaluating weapon system using fuzzy analytic hierarchy process based on entropy weight. Fuzzy sets and systems, 62(2), 127-134.

Saaty, T. (1980). The analytic hierarchy process. New york: Mc Grae-Hill.

Wang, L., Chu, J., & Wu, J. (2007). Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process. International Journal of Production Economics, 107(1), 151-163.

Zimmermann, H. J. (1992). Fuzzy Set Theory and Its Applications Second, Revised Edition. Kluwer academic publishers
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Journal: Management Science Letters | Year: 2014 | Volume: 4 | Issue: 5 | Views: 3823 | Reviews: 0

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