A review of spare parts supply chain management

Authors

  • Zineb Achetoui Laboratory of Engineering, Industrial Management and Innovation, Hassan First University, Faculty of Science and Technology, Settat, Morocco http://orcid.org/0000-0003-2928-3780
  • Charif Mabrouki Laboratory of Engineering, Industrial Management and Innovation, Hassan First University, Faculty of Science and Technology, Settat, Morocco
  • Ahmed Mousrij Laboratory of Engineering, Industrial Management and Innovation, Hassan First University, Faculty of Science and Technology, Settat, Morocco

DOI:

https://doi.org/10.30656/jsmi.v3i2.1524

Keywords:

Spare parts, Forecasting, Classification, Inventory, Supply Chain, Performance

Abstract

The particular characteristics of spare parts have prompted several authors to provide substantial results for effective spare parts supply chain management. In this context, the purpose of this paper is to present the significant contributions that researchers have proposed, over time, for the spare parts supply chain management. The literature has shown that the particular characteristics of spare parts have a significant impact on inventory performance and customer demand fulfillment. For this reason, most of the contributions were focused on spare parts classification methods, forecasting methods and inventory optimization.  The focus of researchers on some areas of spare parts management allowed us to identify some promising perspectives that were not developed in the literature, such as the development of performance measurement frameworks for the spare parts supply chain and the measurement of organizational maturity.  

Downloads

Download data is not yet available.

References

[1] S. M. Wagner and E. Lindemann, “A case study-based analysis of spare parts management in the engineering industry,†Prod. Plan. Control, vol. 19, no. 4, pp. 397–407, June. 2008. doi: 10.1080/09537280802034554.

[2] A. Bacchetti and N. Saccani, “Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice,†Omega, vol. 40, no. 6, pp. 722–737, Dec. 2012. doi: 10.1016/j.omega.2011.06.008.

[3] W. J. Kennedy, J. W. Patterson, and L. D. Fredendall, “An overview of recent literature on spare parts inventories,†Int. J. Prod. Econ., vol. 76, no. 2, pp. 201–215, Mar. 2002. doi: 10.1016/S0925-5273(01)00174-8.

[4] H. Fazlollahtabar, M. Vasiljević, Ž. Stević, and S. Vesković, “Evaluation of supplier criteria in automotive industry using rough AHP,†in The 1st International Conference on Management, Engineering and Environment ICMNEE, pp. 186–197, 2017. https://www.researchgate.net/profile/Zeljko_Stevic/publication/320127427_Evaluation_of_supplier_criteria_in_automotive_industry_using_rough_AHP/links/59cf77a9a6fdcc181acc6d63/Evaluation-of-supplier-criteria-in-automotive-industry-using-rough-AHP.pdf.

[5] D. E. Harter, M. S. Krishnan, and S. A. Slaughter, “Effects of process maturity on quality, cycle time, and effort in software product development,†Manage. Sci., vol. 46, no. 4, pp. 451–466, Apr. 2000. doi: 10.1287/mnsc.46.4.451.12056.

[6] Aberdeen Group, The Engineering Executive’s Strategic Agenda, 2008. https://support.ansys.com/staticassets/ANSYS/staticassets/resourcelibrary/whitepaper/aberdeen-eesa-benchmark.pdf.

[7] M. A. Cohen, N. Agrawal, and V. Agrawal, “Winning in the aftermarket,†Harv. Bus. Rev., vol. 84, no. 5, pp. 129–138, May. 2006. Available at: https://fishmandavidson.wharton.upenn.edu/wp-content/uploads/2016/06/Winning-in-the-Aftermarket_HBR_May_06.pdf.

[8] J. E. Boylan and A. A. Syntetos, “Spare parts management: A review of forecasting research and extensions,†IMA J. Manag. Math., vol. 21, no. 3, pp. 227–237, Jul. 2010. doi: 10.1093/imaman/dpp016.

[9] J. E. Boylan and A. A. Syntetos, “Forecasting for inventory management of service parts,†in Complex System Maintenance Handbook, Springer London, pp. 479–506, 2008. doi: 10.1007/978-1-84800-011-7_20.

[10] M. W. F. M. Draper and A. E. D. Suanet, “Service Parts Logistics Management. In: Supply Chain Management on Demand†An C., Fromm H. (eds). Springer, Berlin, Heidelberg, pp. 187–210, 2005. doi: 10.1007/b138951.

[11] Q. Hu, J. E. Boylan, H. Chen, and A. Labib, “OR in spare parts management: A review,†Eur. J. Oper. Res., vol. 266, no. 2, pp. 395–414, Apr. 2018. doi: 10.1016/j.ejor.2017.07.058.

[12] J. Huiskonen, “Maintenance spare parts logistics: Special characteristics and strategic choices,†Int. J. Prod. Econ., vol. 71, no. 1–3, pp. 125–133, May. 2001. doi: 10.1016/S0925-5273(00)00112-2.

[13] S. Cavalieri, M. Garetti, M. Macchi, and R. Pinto, “A decision-making framework for managing maintenance spare parts,†Prod. Plan. Control, vol. 19, no. 4, pp. 379–396, May. 2008. doi: 10.1080/09537280802034471.

[14] C.-W. Chu, G.-S. Liang, and C.-T. Liao, “Controlling inventory by combining ABC analysis and fuzzy classification,†Comput. Ind. Eng., vol. 55, no. 4, pp. 841–851, Nov. 2008. doi: 10.1016/j.cie.2008.03.006.

[15] P. P. Gajpal, L. S. Ganesh, and C. Rajendran, “Criticality analysis of spare parts using the analytic hierarchy process,†Int. J. Prod. Econ., vol. 35, no. 1–3, pp. 293–297, June. 1994. doi: 10.1016/0925-5273(94)90095-7.

[16] M. A. Sharaf and H. A. Helmy, “A classification model for inventory management of spare parts,†in Proceedings of the 7th international conference on Production, Industrial Engineering, Design and Control (PEDAC), vol. 7, pp. 375–382, 2001. Available at: Google Scholar.

[17] A. A. Syntetos, M. Keyes, and M. Z. Babai, “Demand categorisation in a European spare parts logistics network,†Int. J. Oper. Prod. Manag., vol. 29, no. 3, pp. 292–316, Feb. 2009. doi: 10.1108/01443570910939005.

[18] R. Ramanathan, “ABC inventory classification with multiple-criteria using weighted linear optimization,†Comput. Oper. Res., vol. 33, no. 3, pp. 695–700, Mar. 2006. doi: 10.1016/j.cor.2004.07.014.

[19] P. Zhou and L. Fan, “A note on multi-criteria ABC inventory classification using weighted linear optimization,†Eur. J. Oper. Res., vol. 182, no. 3, pp. 1488–1491, Nov. 2007. doi: 10.1016/j.ejor.2006.08.052.

[20] W. L. Ng, “A simple classifier for multiple criteria ABC analysis,†Eur. J. Oper. Res., vol. 177, no. 1, pp. 344–353, Feb. 2007. doi: 10.1016/j.ejor.2005.11.018.

[21] F. Y. Partovi and M. Anandarajan, “Classifying inventory using an artificial neural network approach,†Comput. Ind. Eng., vol. 41, no. 4, pp. 389–404, Feb. 2002. doi: 10.1016/S0360-8352(01)00064-X.

[22] A. A. Syntetos, J. E. Boylan, and J. D. Croston, “On the categorization of demand patterns,†J. Oper. Res. Soc., vol. 56, no. 5, pp. 495–503, May. 2005, doi: 10.1057/palgrave.jors.2601841.

[23] J. E. Boylan, A. A. Syntetos, and G. C. Karakostas, “Classification for forecasting and stock control: a case study,†J. Oper. Res. Soc., vol. 59, no. 4, pp. 473–481, Apr. 2008. doi: 10.1057/palgrave.jors.2602312.

[24] A. Molenaers, H. Baets, L. Pintelon, and G.Waeyenbergh, “Criticality classification of spare parts: A case study,†Int. J. Prod. Econ., vol. 140, no. 2, pp. 570–578, Dec. 2012. doi: 10.1016/j.ijpe.2011.08.013.

[25] M. Ben Jeddou, “Multi-Criteria ABC Inventory Classification- A Case of Vehicles Spare Parts Items,†J. Adv. Manag. Sci., vol. 2, no. 3, pp. 181–185, Sep. 2014. doi: 10.12720/joams.2.3.181-185.

[26] K. Cobbaert and D. Van Oudheusden, “Inventory models for fast moving spare parts subject to “sudden death†obsolescence,†Int. J. Prod. Econ., vol. 44, no. 3, pp. 239–248, July. 1996. doi: 10.1016/0925-5273(96)00062-X.

[27] R. Dekker, M. J. Kleijn, and P. J. de Rooij, “A spare parts stocking policy based on equipment criticality,†Int. J. Prod. Econ., vol. 56–57, pp. 69–77, Sep. 1998. doi: 10.1016/S0925-5273(97)00050-9.

[28] R. H. Teunter and W. K. Klein Haneveld, “Inventory control of service parts in the final phase,†Eur. J. Oper. Res., vol. 137, no. 3, pp. 497–511, Mar. 2002. doi: 10.1016/S0377-2217(01)00131-X.

[29] M. Kalchschmidt, G. Zotteri, and R. Verganti, “Inventory management in a multi-echelon spare parts supply chain,†Int. J. Prod. Econ., vol. 81–82, pp. 397–413, Jan. 2003. doi: 10.1016/S0925-5273(02)00284-0.

[30] K.-P. Aronis, L. Magou, R. Dekker, and G. Tagaras, “Inventory control of spare parts using a Bayesian approach: A case study,†Eur. J. Oper. Res., vol. 154, no. 3, pp. 730–739, May. 2004. doi: 10.1016/S0377-2217(02)00837-8.

[31] D. Caglar, C.-L. Li, and D. Simchi-Levi, “Two-echelon spare parts inventory system subject to a service constraint,†IIE Trans., vol. 36, no. 7, pp. 655–666, July. 2004. doi: 10.1080/07408170490278265.

[32] P.-L. Chang, Y.-C. Chou, and M.-G. Huang, “A (r, r, Q) inventory model for spare parts involving equipment criticality,†Int. J. Prod. Econ., vol. 97, no. 1, pp. 66–74, July. 2005. doi: 10.1016/j.ijpe.2004.06.048.

[33] H. Wong, D. Cattrysse, and D. Van Oudheusden, “Stocking decisions for repairable spare parts pooling in a multi-hub system,†Int. J. Prod. Econ., vol. 93–94, pp. 309–317, Jan. 2005. doi: 10.1016/j.ijpe.2004.06.029.

[34] E. Porras and R. Dekker, “An inventory control system for spare parts at a refinery: An empirical comparison of different re-order point methods,†Eur. J. Oper. Res., vol. 184, no. 1, pp. 101–132, Jan. 2008. doi: 10.1016/j.ejor.2006.11.008.

[35] D. Louit, R. Pascual, D. Banjevic, and A. K. S. Jardine, “Optimization models for critical spare parts inventories—a reliability approach,†J. Oper. Res. Soc., vol. 62, no. 6, pp. 992–1004, June. 2011. doi: 10.1057/jors.2010.49.

[36] E. Topan, Z. P. Bayındır, and T. Tan, “Heuristics for multi-item two-echelon spare parts inventory control subject to aggregate and individual service measures,†Eur. J. Oper. Res., vol. 256, no. 1, pp. 126–138, Jan. 2017. doi: 10.1016/j.ejor.2016.06.012.

[37] L. Turrini and J. Meissner, “Spare parts inventory management: New evidence from distribution fitting,†Eur. J. Oper. Res., vol. 273, no. 1, pp. 118–130, Feb. 2019. doi: 10.1016/j.ejor.2017.09.039.

[38] S. Makridakis, S. C. Wheelwright and R. J. Hyndman, Forecasting: Methods and Applications. John Wiley & Sons, 1998. https://hephaestus.nup.ac.cy/bitstream/handle/11728/6636/Forecasting-Methods-and-Applications-Table-of-Contents.pdf

[39] N. Altay, F. Rudisill, and L. A. Litteral, “Adapting Wright’s modification of Holt’s method to forecasting intermittent demand,†Int. J. Prod. Econ., vol. 111, no. 2, pp. 389–408, Feb. 2008. doi: 10.1016/j.ijpe.2007.01.009.

[40] J. D. Croston, “Forecasting and Stock Control for Intermittent Demands,†J. Oper. Res. Soc., vol. 23, no. 3, pp. 289–303, Sep. 1972. doi: 10.1057/jors.1972.50.

[41] A. A. Syntetos and J. E. Boylan, “On the bias of intermittent demand estimates,†Int. J. Prod. Econ., vol. 71, no. 1–3, pp. 457–466, May. 2001. doi: 10.1016/S0925-5273(00)00143-2.

[42] R. H. Teunter, A. A. Syntetos, and M. Z. Babai, “Intermittent demand: Linking forecasting to inventory obsolescence,†Eur. J. Oper. Res., vol. 214, no. 3, pp. 606–615, Nov. 2011. doi: 10.1016/j.ejor.2011.05.018.

[43] R. Snyder, “Forecasting sales of slow and fast moving inventories,†Eur. J. Oper. Res., vol. 140, no. 3, pp. 684–699, Aug. 2002. doi: 10.1016/S0377-2217(01)00231-4.

[44] T. R. Willemain, C. N. Smart, and H. F. Schwarz, “A new approach to forecasting intermittent demand for service parts inventories,†Int. J. Forecast., vol. 20, no. 3, pp. 375–387, July. 2004. doi: 10.1016/S0169-2070(03)00013-X.

[45] M. Kalchschmidt, R. Verganti, and G. Zotteri, “Forecasting demand from heterogeneous customers,†Int. J. Oper. Prod. Manag., vol. 26, no. 6, pp. 619–638, June. 2006. doi: 10.1108/01443570610666975.

[46] D. J. Wright, “Forecasting Data Published at Irregular Time Intervals Using an Extension of Holt’s Method,†Manage. Sci., vol. 32, no. 4, pp. 499–510, Apr. 1986. doi: 10.1287/mnsc.32.4.499.

[47] R. Teunter and B. Sani, “On the bias of Croston’s forecasting method,†Eur. J. Oper. Res., vol. 194, no. 1, pp. 177–183, Apr. 2009. doi: 10.1016/j.ejor.2007.12.001.

[48] A. H. C. Eaves and B. G. Kingsman, “Forecasting for the ordering and stock-holding of spare parts,†J. Oper. Res. Soc., vol. 55, no. 4, pp. 431–437, Apr. 2004. doi: 10.1057/palgrave.jors.2601697.

[49] G. Jung, J. Park, Y. Kim, and Y. B. Kim, “A modified bootstrap method for intermittent demand forecasting for rare spare parts,†Int. J. Ind. Eng., vol. 24, no. 2, pp. 245–254, 2017. Available at: Google Scholar.

[50] W. Romeijnders, R. Teunter, and W. van Jaarsveld, “A two-step method for forecasting spare parts demand using information on component repairs,†Eur. J. Oper. Res., vol. 220, no. 2, pp. 386–393, July. 2012. doi: 10.1016/j.ejor.2012.01.019.

[51] R. Verganti, “Order overplanning with uncertain lumpy demand: A simplified theory,†Int. J. Prod. Res., vol. 35, no. 12, pp. 3229–3248, Dec. 1997. doi: 10.1080/002075497194057.

[52] L. Fortuin and H. Martin, “Control of service parts,†Int. J. Oper. Prod. Manag., vol. 19, no. 9, pp. 950–971, Sep. 1999. doi: 10.1108/01443579910280287.

[53] Barkawi and GmbH Partners, Global Study on Spare Parts Logistics. Munich, 2002.

[54] S. De Leeuw and L. Beekman, “Supply chain-oriented performance measurement for automotive spare parts,†Int. J. Automot. Technol. Manag., vol. 8, no. 1, pp. 56–70, 2008. doi: 10.1504/IJATM.2008.018768.

[55] P. Gaiardelli, N. Saccani, and L. Songini, “Performance measurement systems in after-sales service: an integrated framework,†Int. J. Business. Perfo. Manag., vol. 9, no. 2, pp. 145–171, 2007. Available at: Google Scholar.

Downloads

Published

2019-11-18

How to Cite

[1]
Z. Achetoui, C. Mabrouki, and A. Mousrij, “A review of spare parts supply chain management”, j. sist. manaj. ind., vol. 3, no. 2, pp. 67–75, Nov. 2019.

Issue

Vol. 3 No. 2 (2019)

Section

Articles

License

All articles in Jurnal Sistem dan Manajemen Industri can be disseminated provided they include the identity of the article and the source of the article Jurnal Sistem dan Manajemen Industri. The publisher is not responsible for the contents of the article. The content of the article is the sole responsibility of the author

Creative Commons License

Jurnal Sistem dan Manajemen Industri is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Crossref
Scopus
Google Scholar
Europe PMC