Spare Parts Supplier Selection Design: A Case Study of A Railway Company

Robby Ady Asmara; Lien Herliani Kusumah

doi:10.25077/josi.v20.n2.p125-135.2021

Robby Ady Asmara

Universitas Mercu Buana

Lien Herliani Kusumah

Universitas Mercu Buana

Keywords

supply chain management

Abstract

Spare parts support is essential for rolling stock maintenance management. The current supplier selection model determines the selected supplier based on evaluating one aspect of the criteria (product aspect). The selection of suppliers with poor performance occurred between 2018-2020 related to the delivery of goods that exceeded the deadline and goods that did not meet specifications. The first objective of this research is to analyze and determine the relevant priority criteria for selecting suppliers of rolling stock spare parts for railway companies. The second objective is to determine the rolling stock spare parts supplier by using the evaluation criteria determined in the previous process. The method used in this research is the integration of the Fuzzy Delphi Method (FDM), Analytical Hierarchy Process (AHP), and Technique for Others Preference by Similarity to Ideal Solutions (TOPSIS). FDM is used to select important criteria for the selection of suppliers of rolling stock parts. AHP is used to assist in choosing various criteria through evaluation in determining the criteria's weight. TOPSIS is used to assess supplier ratings. A total of 13 criteria from 19 alternative criteria have been selected for railway companies, especially in selecting rolling stock spare parts suppliers. Furthermore, the selection becomes the basis for bidding. Finally, Supplier A is the supplier with the highest relative closeness value (0.591), followed by Supplier B (0.545), and the lowest is Supplier C (0.282).

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References

[1] L. Li, M. Liu, W. Shen, and G. Cheng, "An improved stochastic programming model for supply chain planning of MRO spare parts," Appl. Math. Model., vol. 47, pp. 189–207, 2017, doi: 10.1016/j.apm.2017.03.031.

[2] Bierer, U. Götze, S. Köhler, and R. Lindner, “Control and Evaluation Concept for Smart MRO Approaches,” Procedia CIRP, vol. 40, pp. 699–704, 2016, doi: 10.1016/j.procir.2016.01.157.

[3] M. Seitz, T. Lucht, C. Keller, C. Ludwig, R. Strobelt, and P. Nyhuis, "Improving MRO order processing by means of advanced technological diagnostics and data mining approaches," Procedia Manuf., vol. 43, pp. 688–695, 2020, doi: 10.1016/j.promfg.2020.02.121.

[4] D. Dinis, A. Barbosa-Póvoa, and Â. P. Teixeira, "A supporting framework for maintenance capacity planning and scheduling: Development and application in the aircraft MRO industry," Int. J. Prod. Econ., vol. 218, pp. 1–15, 2019, doi: 10.1016/j.ijpe.2019.04.029.

[5] M. Le Sueur and B. G. Dale, "The procurement of maintenance, repair, and operating supplies: A study of the key problems," Eur. J. Purch. Supply Manag., vol. 4, no. 4, pp. 247–255, 1998, doi: 10.1016/S0969-7012(98)00016-1.

[6] M. Basak, "Achieving E-procurement Benefits in an Aviation MRO Environment," Oper. Supply Chain Manag. An Int. J., vol. 9, no. 1, pp. 50–60, 2015, doi: 10.31387/oscm0230160.

[7] H. H. Turan, M. Atmis, F. Kosanoglu, S. Elsawah, and M. J. Ryan, "A risk-averse simulation-based approach for a joint optimization of workforce capacity, spare part stocks and scheduling priorities in maintenance planning," Reliab. Eng. Syst. Saf., vol. 204, no. March, p. 107199, 2020, doi: 10.1016/j.ress.2020.107199.

[8] S. Van Der Auweraer and R. Boute, "International Journal of Production Economics Forecasting spare part demand using service maintenance information," Intern. J. Prod. Econ., vol. 213, no. April 2018, pp. 138–149, 2019, doi: 10.1016/j.ijpe.2019.03.015.

[9] S. Van Der Auweraer, R. N. Boute, and A. A. Syntetos, "Forecasting spare part demand with installed base information : A review," Int. J. Forecast., vol. 35, no. 1, pp. 181–196, 2019, doi: 10.1016/j.ijforecast.2018.09.002.

[10] S. Zhu, W. Van Jaarsveld, and R. Dekker, “Spare parts inventory control based on maintenance planning,” Reliab. Eng. Syst. Saf., vol. 193, no. January 2019, p. 106600, 2020, doi: 10.1016/j.ress.2019.106600.

[11] C. N. Liao and H. P. Kao, "Supplier selection model using Taguchi loss function, analytical hierarchy process and multi-choice goal programming," Comput. Ind. Eng., vol. 58, no. 4, pp. 571–577, 2010, doi: 10.1016/j.cie.2009.12.004

[12] S. Biruk, P. Jaskowski, and A. Czarnigowska, "Fuzzy AHP for selecting suppliers of construction materials," IOP Conf. Ser. Mater. Sci. Eng., vol. 603, no. 3, 2019, doi: 10.1088/1757-899X/603/3/032093.

[13] R. Kumar, S. S. Padhi, and A. Sarkar, "Supplier selection of an Indian heavy locomotive manufacturer: An integrated approach using Taguchi loss function, TOPSIS, and AHP," IIMB Manag. Rev., vol. 31, no. 1, pp. 78–90, 2019, doi: 10.1016/j.iimb.2018.08.008.

[14] A. M. Li, G. Q. Wang, and J. J. Zhang, "The research on railway construction project materials supplier selection model," Adv. Mater. Res., vol. 919–921, pp. 1503–1508, 2014, doi: 10.4028/www.scientific.net/AMR.919-921.1503.

[15] O. Kilincci and S. A. Onal, "Fuzzy AHP approach for supplier selection in a washing machine company," Expert Syst. Appl., vol. 38, no. 8, pp. 9656–9664, 2011, doi: 10.1016/j.eswa.2011.01.159.

[16] K. C. Lam, R. Tao, and M. C. K. Lam, "A material supplier selection model for property developers using Fuzzy Principal Component Analysis," Autom. Constr., vol. 19, no. 5, pp. 608–618, 2010, doi: 10.1016/j.autcon.2010.02.007.

[17] R. Wang, X. Li, and C. Li, "Optimal selection of sustainable battery supplier for battery-swapping station based on Triangular fuzzy entropy -MULTIMOORA method," J. Energy Storage, vol. 34, no. October, p. 102013, 2021, doi: 10.1016/j.est.2020.102013.

[18] A. Kumar, M. A. Kaviani, A. Hafezalkotob, and E. K. Zavadskas, "Evaluating innovation capabilities of real estate firms: a combined fuzzy Delphi and DEMATEL approach," Int. J. Strateg. Prop. Manag., vol. 21, no. 4, pp. 401–416, 2017, doi: 10.3846/1648715X.2017.1409291.

[19] G. W. Dickson, "An Analysis Of Vendor Selection Systems And Decisions," J. Purch., vol. 2, no. 1, pp. 5–17, 1966, doi: 10.1111/j.1745-493X.1966.tb00818.x.

[20] B. Luzon and S. M. El-Sayegh, "Evaluating supplier selection criteria for oil and gas projects in the UAE using AHP and Delphi," Int. J. Constr. Manag., vol. 16, no. 2, pp. 175–183, 2016, doi: 10.1080/15623599.2016.1146112.

[21] G. Polat and E. Eray, "An Integrated Approach using AHP-ER to Supplier Selection in Railway Projects," Procedia Eng., vol. 123, pp. 415–422, 2015, doi: 10.1016/j.proeng.2015.10.068.

[22] M. Marzouk and M. Sabbah, "AHP-TOPSIS social sustainability approach for selecting supplier in construction supply chain," Clean. Environ. Syst., vol. 2, no. March, p. 100034, 2021, doi: 10.1016/j.cesys.2021.100034

[23] M. Oroojeni, M. Javad, M. Darvishi, A. Oroojeni, and M. Javad, "Green supplier selection for the steel industry using BWM and fuzzy TOPSIS : A case study of Khouzestan steel company," Sustain. Futur., vol. 2, no. October 2019, p. 100012, 2020, doi: 10.1016/j.sftr.2020.100012.

[24] H. Selcuk and A. Selcuk, "Modified two-phase fuzzy goal programming integrated with IF-TOPSIS for green supplier selection," Appl. Soft Comput. J., vol. 93, p. 106371, 2020, doi: 10.1016/j.asoc.2020.106371.

[25] I. Sultana, I. Ahmed, and A. Azeem, "An integrated approach for multiple criteria supplier selection combining Fuzzy Delphi, Fuzzy AHP and Fuzzy TOPSIS," J. Intell. Fuzzy Syst., vol. 29, no. 4, pp. 1273–1287, 2015, doi: 10.3233/IFS-141216.

[26] R. K. Mavi, "Green supplier selection: A fuzzy AHP and fuzzy ARAS approach," Int. J. Serv. Oper. Manag., vol. 22, no. 2, pp. 165–188, 2015, doi: 10.1504/IJSOM.2015.071528.

[27] S. Kumar, S. Kumar, and A. G. Barman, "Supplier selection using fuzzy TOPSIS multi criteria model for a small scale steel manufacturing unit," Procedia Comput. Sci., vol. 133, pp. 905–912, 2018, doi: 10.1016/j.procs.2018.07.097.

[28] S. Sharma and S. Balan, "An integrative supplier selection model using Taguchi loss function, TOPSIS and multi criteria goal programming," J. Intell. Manuf., vol. 24, no. 6, pp. 1123–1130, 2013, doi: 10.1007/s10845-012-0640-y.

[29] Y. Zhang, X. Liu, and H. Bo, "An integrated AHP-entropy approach for spare parts supplier evaluation and order quantity allocation," Adv. Mater. Res., vol. 452–453, pp. 768–772, 2012, doi: 10.4028/www.scientific.net/AMR.452-453.768.

[30] A. K. Kar, "A hybrid group decision support system for supplier selection using analytic hierarchy process, fuzzy set theory and neural network," J. Comput. Sci., vol. 6, pp. 23–33, 2015, doi: 10.1016/j.jocs.2014.11.002.

[31] T. C. Wen, K. H. Chang, and H. H. Lai, "Integrating the 2-tuple linguistic representation and soft set to solve supplier selection problems with incomplete information," Eng. Appl. Artif. Intell., vol. 87, no. August 2019, p. 103248, 2020, doi: 10.1016/j.engappai.2019.103248.

[32] S. Sarkar, D. K. Pratihar, and B. Sarkar, "An integrated fuzzy multiple criteria supplier selection approach and its application in a welding company," J. Manuf. Syst., vol. 46, pp. 163–178, 2018, doi: 10.1016/j.jmsy.2017.12.004.

[33] A. E. Cengiz, O. Aytekin, I. Ozdemir, H. Kusan, and A. Cabuk, "A Multi-criteria Decision Model for Construction Material Supplier Selection," Procedia Eng., vol. 196, no. June, pp. 294–301, 2017, doi: 10.1016/j.proeng.2017.07.202.

[34] M. Tavana, A. Fallahpour, D. Di Caprio, and F. J. Santos-Arteaga, "A hybrid intelligent fuzzy predictive model with simulation for supplier evaluation and selection," Expert Syst. Appl., vol. 61, pp. 129–144, 2016, doi: 10.1016/j.eswa.2016.05.027.

[35] E. Plebankiewicz and D. Kubek, "Multicriteria Selection of the Building Material Supplier Using AHP and Fuzzy AHP," J. Constr. Eng. Manag., vol. 142, no. 1, p. 04015057, 2016, doi: 10.1061/(ASCE)CO.1943-7862.0001033.

[36] G. N. Yücenur, Ö. Vayvay, and N. Ç. Demirel, "Supplier selection problem in global supply chains by AHP and ANP approaches under fuzzy environment," Int. J. Adv. Manuf. Technol., vol. 56, no. 5–8, pp. 823–833, 2011, doi: 10.1007/s00170-011-3220-y.

[37] R. Gupta, A. Sachdeva, and A. Bhardwaj, "Selection of 3pl Service Provider using Integrated Fuzzy Delphi and Fuzzy TOPSIS," Lect. Notes Eng. Comput. Sci., vol. 2187, no. 1, pp. 1092–1097, 2010.

[38] Y. K. Fu, "An integrated approach to catering supplier selection using AHP-ARAS-MCGP methodology," J. Air Transp. Manag., vol. 75, no. July 2018, pp. 164–169, 2019, doi: 10.1016/j.jairtraman.2019.01.011

[39] M. Zeydan, C. Çolpan, and C. Çobanoģlu, "A combined methodology for supplier selection and performance evaluation," Expert Syst. Appl., vol. 38, no. 3, pp. 2741–2751, 2011, doi: 10.1016/j.eswa.2010.08.064.

[40] A. Ishikawa, M. Amagasa, T. Shiga, G. Tomizawa, R. Tatsuta, and H. Mieno, "The max-min Delphi method and fuzzy Delphi method via fuzzy integration," Fuzzy Sets Syst., vol. 55, no. 3, pp. 241–253, 1993, doi: 10.1016/0165-0114(93)90251-C.

[41] L. A. Zadeh, "Fuzzy sets," Inf. Control, vol. 8, no. 3, pp. 338–353, 1965, doi: 10.1016/S0019-9958(65)90241-X. 10.1016/S0019-9958(65)90241-X

[42] S. Ebrahimi and R. Bridgelall, "A fuzzy Delphi analytic hierarchy model to rank factors influencing public transit mode choice: A case study," Res. Transp. Bus. Manag., no. May, p. 100496, 2020, doi: 10.1016/j.rtbm.2020.10049696.

[43] T. Y. Pham, H. M. Ma, and G. T. Yeo, "Application of Fuzzy Delphi TOPSIS to Locate Logistics Centers in Vietnam: The Logisticians' Perspective," Asian J. Shipp. Logist., vol. 33, no. 4, pp. 211–219, 2017, doi: 10.1016/j.ajsl.2017.12.004.

[44] C. Lin, "Application of fuzzy Delphi method (FDM) and fuzzy analytic hierarchy process (FAHP) to criteria weights for fashion design scheme evaluation," Int. J. Cloth. Sci. Technol., vol. 25, no. 3, pp. 171–183, 2013, doi: 10.1108/09556221311300192.

[45] H. Jones and B. C. Twiss, "Forecasting technology for planning decisions," 1978. doi: 10.1007/978-1-349-03134-4.

[46] N. K. Ismail, S. Mohamed, and M. I. Hamzah, "The Application of the Fuzzy Delphi Technique to the Required Aspect of Parental Involvement in the Effort to Inculcate Positive Attitude among Preschool Children," Creat. Educ., vol. 10, no. 12, pp. 2907–2921, 2019, doi: 10.4236/ce.2019.1012216.

[47] P. L. Chang, C. W. Hsu, and P. C. Chang, "Fuzzy Delphi method for evaluating hydrogen production technologies," Int. J. Hydrogen Energy, vol. 36, no. 21, pp. 14172–14179, 2011, doi: 10.1016/j.ijhydene.2011.05.045.

[48] S. K. Manakandan, R. Ismai, M. R. M. Jamil, and P. Ragunath, "Pesticide applicators questionnaire content validation: A fuzzy delphi method," Med. J. Malaysia, vol. 72, no. 4, pp. 228–235, 2017.

[49] T. L. Saaty, "How to make a decision: The analytic hierarchy process," Eur. J. Oper. Res., vol. 48, no. 1, pp. 9–26, 1990, doi: 10.1016/0377-2217(90)90057-I.

[50] C. L. Hwang and K. Yoon, "Multiple Attributes Decision Making Methods and Applications, spring," New York, 1981. doi: 10.1007/978-3-642-48318-9_3.

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Published

Nov 29, 2021

https://doi.org/10.25077/josi.v20.n2.p125-135.2021

How to Cite

[1]

R. A. Asmara and L. H. Kusumah, “Spare Parts Supplier Selection Design: A Case Study of A Railway Company”, J. Optimasi Sist. Ind., vol. 20, no. 2, pp. 125–135, Nov. 2021.

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Vol. 20 No. 2 (2021): Published in November 2021

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