Spare Part Management Using Economic Order Quantity Model With Fuzzy-Analytical Hierarchy Process (Fuzzy-AHP) Optimization

Maintenance is one of the pillar in developing world class manufacturing. One of the accountability of maintenance team is the control of spare parts inventory. For a high transaction spare part, controlling the correct quantity is a real challenge. Several methods have been proposed by researchers...

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Main Author:	Kamaludin, Khairun Najmi
Format:	Thesis
Language:	English English
Published:	2019
Subjects:	T Technology (General) TS Manufactures
Online Access:	http://eprints.utem.edu.my/id/eprint/24958/1/Spare%20Part%20Management%20Using%20Economic%20Order%20Quantity%20Model%20With%20Fuzzy-Analytical%20Hierarchy%20Process%20%28Fuzzy-Ahp%29%20Optimization.pdf http://eprints.utem.edu.my/id/eprint/24958/2/Spare%20Part%20Management%20Using%20Economic%20Order%20Quantity%20Model%20With%20Fuzzy-Analytical%20Hierarchy%20Process%20%28Fuzzy-Ahp%29%20Optimization.pdf
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id	my-utem-ep.24958
record_format	uketd_dc
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Abdullah, Lokman
topic	T Technology (General) TS Manufactures
spellingShingle	T Technology (General) TS Manufactures Kamaludin, Khairun Najmi Spare Part Management Using Economic Order Quantity Model With Fuzzy-Analytical Hierarchy Process (Fuzzy-AHP) Optimization
description	Maintenance is one of the pillar in developing world class manufacturing. One of the accountability of maintenance team is the control of spare parts inventory. For a high transaction spare part, controlling the correct quantity is a real challenge. Several methods have been proposed by researchers to cater the issue. Owing to this reason, this project investigates economic order quantity (EOQ) application in a spare part management and inventory, and optimization of EOQ with Fuzzy Logic Analytic Hierarchy Process AHP (Fuzzy AHP). The objective is to determine the best combination of material and fabricator of a specified spare part using AHP and triangular and trapezoidal Fuzzy AHP. EOQ model was used to quantify the ideal quantity of the spare part to be purchased. For the three AHP models, five main criteria were used to decide; cost, quality, productivity, delivery time and quantity, and to support, another sets of sub-criteria to the five criteria as mentioned. Eight solutions or alternatives were to be chosen from. One of the alternative from the AHP hierarchy, has consistently been produced as the result calculated from AHP and Fuzzy AHP. Based on the final result, it is recorded that the first rank is alternative 8 (OPTION 8), thus for AHP is at 16.466%, triangular AHP at 13.115% and trapezoidal AHP at 13.332%. This consolidate that Fuzzy AHP are able to support AHP result with the correct data analyzed. From this alternative, an EOQ model is calculated, and then simulated in a visual form for a time period. Numerical examples are provided to illustrate the model from a case study. 87 pieces of the spare part is suggested as the EOQ for the specified part. Other quantity such as maximum quantity, minimum quantity and ordering point were also defined. Other decision making tool such as Analytic Network Process (ANP), AHP with Technique for Order of Preference by Similarity to Ideal Solution (AHP-TOPSIS) and Preference Ranking Organization Method for Enrichment of Evaluations (Promethee) are extensions for this research. Finally, industrial application is in the best interest to fully understand the impact of this research.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Kamaludin, Khairun Najmi
author_facet	Kamaludin, Khairun Najmi
author_sort	Kamaludin, Khairun Najmi
title	Spare Part Management Using Economic Order Quantity Model With Fuzzy-Analytical Hierarchy Process (Fuzzy-AHP) Optimization
title_short	Spare Part Management Using Economic Order Quantity Model With Fuzzy-Analytical Hierarchy Process (Fuzzy-AHP) Optimization
title_full	Spare Part Management Using Economic Order Quantity Model With Fuzzy-Analytical Hierarchy Process (Fuzzy-AHP) Optimization
title_fullStr	Spare Part Management Using Economic Order Quantity Model With Fuzzy-Analytical Hierarchy Process (Fuzzy-AHP) Optimization
title_full_unstemmed	Spare Part Management Using Economic Order Quantity Model With Fuzzy-Analytical Hierarchy Process (Fuzzy-AHP) Optimization
title_sort	spare part management using economic order quantity model with fuzzy-analytical hierarchy process (fuzzy-ahp) optimization
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Manufacturing Engineering
publishDate	2019
url	http://eprints.utem.edu.my/id/eprint/24958/1/Spare%20Part%20Management%20Using%20Economic%20Order%20Quantity%20Model%20With%20Fuzzy-Analytical%20Hierarchy%20Process%20%28Fuzzy-Ahp%29%20Optimization.pdf http://eprints.utem.edu.my/id/eprint/24958/2/Spare%20Part%20Management%20Using%20Economic%20Order%20Quantity%20Model%20With%20Fuzzy-Analytical%20Hierarchy%20Process%20%28Fuzzy-Ahp%29%20Optimization.pdf
_version_	1747834106321829888
spelling	my-utem-ep.249582021-09-29T12:25:07Z Spare Part Management Using Economic Order Quantity Model With Fuzzy-Analytical Hierarchy Process (Fuzzy-AHP) Optimization 2019 Kamaludin, Khairun Najmi T Technology (General) TS Manufactures Maintenance is one of the pillar in developing world class manufacturing. One of the accountability of maintenance team is the control of spare parts inventory. For a high transaction spare part, controlling the correct quantity is a real challenge. Several methods have been proposed by researchers to cater the issue. Owing to this reason, this project investigates economic order quantity (EOQ) application in a spare part management and inventory, and optimization of EOQ with Fuzzy Logic Analytic Hierarchy Process AHP (Fuzzy AHP). The objective is to determine the best combination of material and fabricator of a specified spare part using AHP and triangular and trapezoidal Fuzzy AHP. EOQ model was used to quantify the ideal quantity of the spare part to be purchased. For the three AHP models, five main criteria were used to decide; cost, quality, productivity, delivery time and quantity, and to support, another sets of sub-criteria to the five criteria as mentioned. Eight solutions or alternatives were to be chosen from. One of the alternative from the AHP hierarchy, has consistently been produced as the result calculated from AHP and Fuzzy AHP. Based on the final result, it is recorded that the first rank is alternative 8 (OPTION 8), thus for AHP is at 16.466%, triangular AHP at 13.115% and trapezoidal AHP at 13.332%. This consolidate that Fuzzy AHP are able to support AHP result with the correct data analyzed. From this alternative, an EOQ model is calculated, and then simulated in a visual form for a time period. Numerical examples are provided to illustrate the model from a case study. 87 pieces of the spare part is suggested as the EOQ for the specified part. Other quantity such as maximum quantity, minimum quantity and ordering point were also defined. Other decision making tool such as Analytic Network Process (ANP), AHP with Technique for Order of Preference by Similarity to Ideal Solution (AHP-TOPSIS) and Preference Ranking Organization Method for Enrichment of Evaluations (Promethee) are extensions for this research. Finally, industrial application is in the best interest to fully understand the impact of this research. 2019 Thesis http://eprints.utem.edu.my/id/eprint/24958/ http://eprints.utem.edu.my/id/eprint/24958/1/Spare%20Part%20Management%20Using%20Economic%20Order%20Quantity%20Model%20With%20Fuzzy-Analytical%20Hierarchy%20Process%20%28Fuzzy-Ahp%29%20Optimization.pdf text en public http://eprints.utem.edu.my/id/eprint/24958/2/Spare%20Part%20Management%20Using%20Economic%20Order%20Quantity%20Model%20With%20Fuzzy-Analytical%20Hierarchy%20Process%20%28Fuzzy-Ahp%29%20Optimization.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=117927 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Manufacturing Engineering Abdullah, Lokman 1. Aissaoui N., Haouari M.,, Hassini E., 2007. Supplier selection and order lot sizing modeling: A review , Computers & Operations Research 34, pp. 3516 – 3540 2. Ariff H., Salit M. 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Spare parts management: a review of forecasting research and extensions, IMA Journal of Management Mathematics (2010) 21, pp. 227−237 8. Chan F., Kumar N., 2005. Global supplier development considering risk factors using fuzzy extended AHP-based approach, Omega International Journal of Management Science 35 (2007) 417 – 431 9. Chang H.C, 2004. An application of fuzzy sets theory to the EOQ model with imperfect quality items, Computers & Operations Research 31, pp. 2079–2092 10. Choi T.M, 2013. Handbook of EOQ Inventory Problems, Springer Dordrecht Heidelberg London 11. Digiesi S., G. Mossa G., Rubino S., 2014. A sustainable EOQ model for repairable spare parts under uncertain demand, IMA Journal of Management Mathematics (2014) Vol 26, Issue 2, April 2015, pp. 185–203 12. Ghodsypour S.H., O’Brien C., 1996. A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming , Int. J. Production Economics 56-57 (1998) pp. 199-212 13. Hamdan S., Cheaitou A., 2015. Green Supplier Selection and Order Allocation Using an Integrated Fuzzy TOPSIS, AHP and IP Approach, 2015 International Conference on Industrial Engineering and Operations Management (IEOM) 14. Ilgın M. A. , 2019. A spare parts criticality evaluation method based on fuzzy AHP and Taguchi loss functions, Mainten ance and Reliability Vol. 21, No. 1, 2019, pp. 145-152 15. Jitrawichawet, S.,Sarfaraz, A. and Jenab, K. 2013. Reliability-based foreign supplier selection using Fuzzy AHP , Int. J. Applied Decision Sciences, Vol. 6, No. 3 pp.245–262. 16. Kahraman C., Cebeci U., Ulukan Z., 2003. Multi-criteria supplier selection using fuzzy AHP, Logistics Information Management Volume 16 • Number 6 • 2003 • pp. 382-394 17. Kamaludin, KN., Abdullah, L., Maslan, MN., Zamri, R., Ali, MM. & Syed Mohamad, MS. 2019. Utilization of Analytical Hierarchy Process (AHP) for selecting the best design concept of conveyor system. Lecture Notes in Mechanical Engineering, pp. 265–279. 18. Kennedy W.J. , Wayne Patterson J. ,Fredendall L. D., 2001. An overview of recent literature on spare parts inventories, International Journal of Production Economics, 76 (2002) pp. 201–215 19. Khalilpourazari S., Pasandideh S.H.R., 2018. Modelling and optimization of multi-item multi-constrained EOQ model for growing items, Knowledge-Based Systems ,Volume 164, pp. 150-162 20. Khodadadi S., Kumar B., 2013. Contractor selection with risk assessment by using AHP-Fuzzy method, International Journal of Advances in Engineering & Technology, Jan. 2013. Vol. 5, Issue 2, pp. 311-318 21. Kreng V., Wu C., 2006. Evaluation of knowledge portal development tools using a fuzzy AHP approach: The case of Taiwanese stone industry, European Journal of Operational Research 176 (2007) pp. 1795–1810 22. Lengu D., Syntetos A.A, Babai M.Z., 2014. Spare parts management: Linking distributional assumptions to demand classification, European Journal of Operational Research Vol. 235 (2014) pp. 624–635 23. Nakajima S., 1983, Introduction to TPM, Productivity Press Inc, Portland, Orlando Nydick R. L. and Hill R. P, 1992. Using the Analytic Hierarchy Process to Structure the Supplier Selection Procedure, International Journal of Purchasing and Materials management, Vol 28, Issue 2, pp. 31-36 24. Özdağoğlu A. , Özdağoğlu G., 2007. Comparison of AHP and Fuzzy AHP for the multi criteria decision making process with linguistic evaluations. Istanbul Ticaret Üniversitesi Fen Bilimleri Dergisi Yıl, pp. 65–85. 25. Pałucha K., 2012. World Class Manufacturing model in production management, Archives of Materials Science and Engineering, 58/2 , pp. 227-234. 26. Porras E., Dekker R., 2007. An inventory control system for spare parts at a refinery:An empirical comparison of different re order point methods, European Journal of Operational Research Vol. 184 (2008), pp. 101–132 27. Rego J. R, Mesquita M.A, 2010. Spare parts inventory control: a literature review, Journal of SciELO Analytics, vol.21, n.4, pp.645-666 28. Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill. 29. Sanni S., O'Neill B., 2018. Inventory optimisation in a three parameter Weibull model under a prepayment system, Computers & Industrial Engineering 128 (2019), pp. 298–304 30. Scott C. , Lundgren H., Thompson P., 2018, Guide to Supply Chain Management, Springer International Publishing. 31. Singh T., Mallick C. Singh R. K., 2018. Formulating an Economic order quantity Model for Items with Variable Rate of Deterioration and Two-Component Demand, Soft Computing for Problem Solving, pp. 273-282 32. Stevenson W.J. 2014, Operation Management, McGraw-Hill Series in Operations and Decision Sciences. 33. Wagner S.M., Lindemann E., 2008. A case study-based analysis of spare parts management in the engineering industry, Production Planning & Control: The Management of Operations, 19:4, pp. 397-407 34. Zaki, A., Noor, M., Jafar, F. A., & Zainudin, S. F., 2017. Fusion Of Fuzzy Ahp In Selecting Material For Drinking Water Bottle Based On Customer Needs, ARPN Journal of Engineering and Applied Science 12(14), pp. 4243–4249. 35. Zheng, G., Zhu, N., Tian, Z., Chen, Y., & Sun, B. 2012. Application of a trapezoidal fuzzy AHP method for work safety evaluation and early warning rating of hot and humid environments. Safety Science, 50(2), pp. 228–239.

Spare Part Management Using Economic Order Quantity Model With Fuzzy-Analytical Hierarchy Process (Fuzzy-AHP) Optimization

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