Dergiler / Gazi University Journal of Science / 2025 / Volume: 38 Issue: 4

A Systematic Literature Review on Spare Parts Classification, Inventory and Warehouse Management from Maintenance-Repair Perspective

Metin İfraz(GAZİ ÜNİVERSİTESİ)0000-0001-7161-223X
Semra Tebrizcik(KIRIKKALE ÜNİVERSİTESİ)0000-0002-2984-7403
Adnan Aktepe(KIRIKKALE ÜNİVERSİTESİ)0000-0002-3340-244X
Süleyman Ersöz(KIRIKKALE ÜNİVERSİTESİ)0000-0002-7534-6837
Ahmet Kürşad Türker(KIRIKKALE ÜNİVERSİTESİ)0000-0001-6686-9241
Sayfa
—
Yayın Tarihi
2025-12-01
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

While new technologies such as blockchain and internet of things offer high potential for warehouse traceability, inventory movements, their adoption remains limited.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Inventory management is becoming a critical aspect of maintenance-repair businesses.
📊
Temel Bulgular & Veri:The primary focus of this study is the literature on spare parts classification, inventory management, and warehouse management in the maintenance and repair industry over the last 14 years.
💡
Sonuç & Katkı:While new technologies such as blockchain and internet of things offer high potential for warehouse traceability, inventory movements, their adoption remains limited.
🔬Tür:Literatür & Derleme Çalışması
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Inventory management · Inventory classification · Warehouse management

Abstract

Inventory management is becoming a critical aspect of maintenance-repair businesses. The goal of companies is to minimize inventory costs while maximizing service levels. The ability to perform these two conflicting situations at the optimum level provides various benefits to enterprises. This study offers a systematic literature review on spare parts management. The primary focus of this study is the literature on spare parts classification, inventory management, and warehouse management in the maintenance and repair industry over the last 14 years. The Systematic Literature Review included 118 studies that met the predetermined criteria and were examined within the framework of our research questions. We presented an overview of statistics, goals, inputs, methods, and findings. In addition, this study offers suggestions for future research by pointing to subjects that have not yet been studied or understudied in the literature. The variety of inputs in classification studies is increasing. While traditional inputs include cost, lead times, demand, usage, and failure rates, recent studies integrate strategic criteria such as supplier predictability, inventory policies, and order replenishment frequency. Classic methods considering criteria such as cost and criticality remain prevalent, while multi-criteria and machine learning techniques are increasingly applied. In inventory management studies, inventory and maintenance planning are mostly addressed separately, and the focus is frequently on cost minimization. Considering stochastic demand, joint maintenance and inventory planning, and multi-objective optimization may yield improvements. While new technologies such as blockchain and internet of things offer high potential for warehouse traceability, inventory movements, their adoption remains limited.

🔖

Bu Makaleye Atıf Yap

İfraz, M., Tebrizcik, S., Aktepe, A., Ersöz, S., Türker, A. K. (2025). A Systematic Literature Review on Spare Parts Classification, Inventory and Warehouse Management from Maintenance-Repair Perspective. Gazi University Journal of Science, Volume: 38 Issue: 4. https://doi.org/10.35378/gujs.1484883

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (134)

  1. İfraz, M., Aktepe, A., Ersöz, S., and Çetinyokuş, T., “Demand Forecasting of Spare Parts with Regression and Machine Learning Methods: Application in a Bus Fleet”, Journal of Engineering Research, 100057, (2023). DOI: https://doi.org/10.1016/j.jer.2023.100057
  2. Jiang, Y., Chen, M., and Zhou, D., “Joint optimization of preventive maintenance and inventory policies for multi-unit systems subject to deteriorating spare part inventory”, Journal of Manufacturing Systems, 35: 191-205, (2015). DOI: https://doi.org/10.1016/j.jmsy.2015.01.002
  3. Burns, N. and Grove, S. K., “Understanding nursing research: Building an evidence-based practice, 4 nd Ed.”, China: Saunders, (2007).
  4. Hemingway, P., and Brereton, N., Access Date: 10.02.2023 http://www.bandolier.org.uk/painres/download/whatis/Syst-review.pdf, (2009).
  5. Moula, P., and Goodman M., “Nursing research”, London: SAGE Publication Ltd, (2009).
  6. Aria, M., and Cuccurullo, C., “bibliometrix: An R-tool for comprehensive science mapping analysis”, Journal of Informetrics, 11(4): 959-975, (2017). DOI: https://doi.org/10.1016/j.joi.2017.08.007
  7. Train, K. E., “Discrete choice methods with simulation”, Cambridge University Press, (2009).
  8. Ersöz, O. O., İnal, A. F., Aktepe, A., Türker, A. K., and Ersöz, S., “A Systematic Literature Review of the Predictive Maintenance from Transportation Systems Aspect”, Sustainability, 14(21): 14536, (2022). DOI: https://doi.org/10.3390/su142114536
  9. Kulshrestha, N., Agrawal, S., and Shree, D., “Spare parts management in industry 4.0 era: a literature review”, Journal of Quality in Maintenance Engineering, 30(1): 248-283, (2024). DOI: https://doi.org/10.1108/jqme-04-2023-0037
  10. Yalçınkaya, O., and Karadaş, Y., “ABC Analysis and Simulation Modeling of Order Process in an Automotive Spare Parts Company”, Dokuz Eylul University Faculty of Engineering Journal of Science and Engineering, 22(64): 287-300, (2020). DOI: https://doi.org/10.21205/deufmd.2020226428
  11. Torre, N. M. M., Salomon, V. A. P., and Florek-Paszkowska, A. K., “Multi-criteria classification of spare parts in the steel industry”, Brazilian Journal of Operations and Production Management, 22(1): 2344-2344, (2025). DOI: https://doi.org/10.14488/bjopm.2344.2025
  12. Teixeira, C., Lopes, I., and Figueiredo, M., “Spare Parts Stock Management: Classification and Policy Assignment”, Faculty of Mechanical Engineering Transactions, 52(2): (2024). DOI: https://doi.org/10.5937/fme2402257t
  13. Nafiurridha, and Choiruddin, A., “Classifying MRP Strategy of Aircraft Spare Parts Using Supervised Machine Learning”, Procedia Computer Science, 234: 470–477, (2024). DOI: https://doi.org/10.1016/j.procs.2024.03.029
  14. Yavuz, A., “Spare part classification and inventory control improvement for case company”, (2023).
  15. Sheikh-Zadeh, A., Scott, M. A., and Enayaty-Ahangar, F., “The role of prescriptive data and non-linear dimension-reduction methods in spare part classification”, Computers and Industrial Engineering, 175: 108912, (2023). DOI: https://doi.org/10.1016/j.cie.2022.108912
  16. Cakmak, E., and Guney, E., “Spare parts inventory classification using Neutrosophic Fuzzy EDAS method in the aviation industry”, Expert Systems with Applications, 224: 120008, (2023). DOI: https://doi.org/10.1016/j.eswa.2023.120008
  17. Sudarmaji, A. H. S., “Failure Mode and Effect Analysis Implementation for Spare Part Classification and Inventory Management in Automotive Manufacturing (Case Study of Pt. XYZ)”, (2022). DOI: https://doi.org/10.5281/zenodo.6463291
  18. Sheikh-Zadeh, A., Rossetti, M. D., and Scott, M. A., “Performance-based inventory classification methods for large-Scale multi-echelon replenishment systems”, Omega, 101: 102276, (2021). DOI: https://doi.org/10.1016/j.omega.2020.102276
  19. Yang, K., Wang, Y., Fan, S., and Mosleh, A., “Multi-criteria spare parts classification using the deep convolutional neural network method”, Applied Sciences, 11(15): 7088, (2021). DOI: https://doi.org/10.3390/app11157088
  20. Lopes, I. D. S., Figueiredo, M., and Sá, V., “Criticality evaluation to support maintenance management of manufacturing systems”, International Journal of Industrial Engineering and Management, 11 (1): 3–18, (2020). DOI: https://doi.org/10.24867/ijiem-2020-1-248
  21. Yeşilkayalı, S., “Integrated classification methods for spare parts: A case study on a mass production factory”, (2020).
  22. Boström, E., and Lundell, J., “Availability vs. Cost Efficiency: A Case Study Taking on an Integrated Approach to Spare Part Distribution in the High-Tech Industry”, (2020).
  23. Bilir, C., and Erbaş, M. A., “Joint Maintenance and Inventory Optimızation: An Applıcation in An Airline Company”, Business & Management Studies: An International Journal, 7(2): 814, (2019). DOI: https://doi.org/10.15295/bmij.v7i2.1109
  24. Chen, J., Gusikhin, O., Finkenstaedt, W., and Liu, Y. N., “Maintenance, repair, and operations parts inventory management in the era of industry 4.0”, International Federation of Automatic Control-PapersOnLine, 52(13): 171-176, (2019). DOI: https://doi.org/10.1016/j.ifacol.2019.11.171
  25. Teixeira, C. P., Tereso, A. P., Lopes, I. D. S., and Figueiredo, M., “A comparison of multi-criteria methods for spare parts classification”, (2019).
  26. Aktepe, A., Türker, A. K., Ersöz, S., Dalgıç, A., and Barışcı, N., “An inventory classification approach combining expert systems, clustering, and fuzzy logic with the ABC method, and an application”, South African Journal of Industrial Engineering, 29(1): 49-62, (2018). DOI: https://doi.org/10.7166/29-1-1784
  27. Lolli, F., Ishizaka, A., Gamberini, R., Balugani, E., and Rimini, B., “Decision trees for supervised multi-criteria inventory classification”, Procedia Manufacturing, 11: 1871-1881, (2017). DOI: https://doi.org/10.1016/j.promfg.2017.07.326
  28. Nurcahyo, R., and Malik, F. M., “Aircraft spare parts inventory management using multi-criteria classification with AHP approach”, 4th IEEE International Conference on Engineering Technologies and Applied Sciences (ICETAS), 1-5, (2017). DOI: https://doi.org/10.1109/icetas.2017.8277890
  29. Güner Gören, H., and Dağdeviren, O., “An excel-based inventory control system based on ABC and VED analyses for pharmacy: a case study”, Galore International Journal of Health Sciences and Research, 2(1): 11-17, (2017).
  30. Ayat, M., “A Case Study of Spare Parts Inventory of Printing Industry using ABC and VED analysis”, Merit Research Journals, 5(1): 001-007, (2017).
  31. Teixeira, C., Lopes, I., and Figueiredo, M., “Multi-criteria classification for spare parts management: A case study”, Procedia Manufacturing, 11: 1560-1567, (2017). DOI: https://doi.org/10.1016/j.promfg.2017.07.295
  32. Hu, Q., Chakhar, S., Siraj, S., and Labib, A., “Spare parts classification in industrial manufacturing using the dominance-based rough set approach”, European Journal of Operational Research, 262(3): 1136-1163, (2017). DOI: https://doi.org/10.1016/j.ejor.2017.04.040
  33. Antosz, K., and Ratnayake, R. C., “Classification of spare parts as the element of a proper realization of the machine maintenance process and logistics-case study”, International Federation of Automatic Control-PapersOnLine, 49(12): 1389-1393, (2016). DOI: https://doi.org/10.1016/j.ifacol.2016.07.760
  34. Baykasoğlu, A., Subulan, K., and Karaslan, F. S., “A new fuzzy linear assignment method for multi-attribute decision making with an application to spare parts inventory classification”, Applied Soft Computing, 42: 1-17, (2016). DOI: https://doi.org/10.1016/j.asoc.2016.01.031
  35. Kartal, H., Öztekin, A., Gunasekaran, A., and Cebi, F., “An integrated decision analytic framework of machine learning with multi-criteria decision making for multi-attribute inventory classification”, Computers & Industrial Engineering, 101: 599-613, (2016). DOI: https://doi.org/10.1016/j.cie.2016.06.004
  36. Stoll, J., Kopf, R., Schneider, J., and Lanza, G., “Criticality analysis of spare parts management: a multi-criteria classification regarding a cross-plant central warehouse strategy”, Production Engineering, 9(2): 225-235, (2015). DOI: https://doi.org/10.1007/s11740-015-0602-2
  37. Lolli, F., Ishizaka, A., and Gamberini, R., “New AHP-based approaches for multi-criteria inventory classification”, International Journal of Production Economics, 156: 62-74, (2014). DOI: https://doi.org/10.1016/j.ijpe.2014.05.015
  38. Özkan, G., “Identifyıng Critical Maıntenance Parts With Soft Computing Algorithms”, PhD. Thesis, University of Kocaeli, (2014).
  39. Aisyati, A., Jauhari, W. A., and Rosyidi, C. N., “Determination inventory level for aircraft spare parts using continuous review model”, International Journal of Business Research and Management (IJBRM), 4(1), 1-12, (2013).
  40. Aydın Keskin, G., and Özkan, C., “Multiple criteria ABC analysis with FCM clustering”, Journal of Industrial Engineering, (2013). DOI: https://doi.org/10.1155/2013/827274
  41. Molenaers, A., Baets, H., Pintelon, L., and Waeyenbergh, G., “Criticality classification of spare parts: A case study”, International Journal of Production Economics, 140(2): 570-578, (2012). DOI: https://doi.org/10.1016/j.ijpe.2011.08.013
  42. Guarnotta, G., “Industrial Vehicles’ Inventory Management using Data-Driven Stochastic Optimization and Forecasting”, PhD. Thesis, Politecnico di Torino, (2022).
  43. Zhang, J., Zhao, X., Song, Y., and Qiu, Q., “Joint optimization of condition-based maintenance and spares inventory for a series–parallel system with two failure modes”, Computers & Industrial Engineering, 168: 108094, (2022). DOI: https://doi.org/10.1016/j.cie.2022.108094
  44. Zhang, J. X., Du, D. B., Si, X. S., Hu, C. H., and Zhang, H. W., “Joint optimization of preventive maintenance and inventory management for standby systems with hybrid-deteriorating spare parts”, Reliability Engineering and System Safety, 214: 107686, (2021). DOI: https://doi.org/10.1016/j.ress.2021.107686
  45. Portal-Garcia, M., Vera-Cabello, R., Quiroz, J., Marcelo, G., and Alvarez, J. C., “Integrated Model of Maintenance Management and Inventory System in a Fleet of Trucks”, 10th International Conference on Industrial Technology and Management, 172-176, (2021). DOI: https://doi.org/10.1109/icitm52822.2021.00038
  46. Zhu, S., van Jaarsveld, W., and Dekker, R., “Spare parts inventory control based on maintenance planning”, Reliability Engineering and System Safety, 193: 106600, (2020). DOI: https://doi.org/10.1016/j.ress.2019.106600
  47. Liu, Q., Dong, M., Chen, F. F., Liu, W., and Ye, C., “Multi-objective imperfect maintenance optimization for production system with an intermediate buffer”, Journal of Manufacturing Systems, 56: 452-462, (2020). DOI: https://doi.org/10.1016/j.jmsy.2020.07.002
  48. Kafiabad, S. T., Zanjani, M. K., and Nourelfath, M., “Integrated planning of operations and on-job training in maintenance logistics networks”, Reliability Engineering and System Safety, 199: 106922, (2020). DOI: https://doi.org/10.1016/j.ress.2020.106922
  49. Al-Momani, H., Al Meanazel, O. T., Kwaldeh, E., Alaween, A., Khasaleh, A., and Qamar, A., “The efficiency of using a tailored inventory management system in the military aviation industry”, Heliyon, 6(7): e04424, (2020). DOI: https://doi.org/10.1016/j.heliyon.2020.e04424
  50. Yuvaraj, K., Oorappan, G. M., Megavarthini, K. K., Pravin, M. C., Adharsh, R., and Kumaran, M. A., “Design And Development Of An Application For Database Maintenance In Inventory Management System Using Tkinter And Sqlite Platform”, In IOP Conference Series: Materials Science and Engineering, 995 (1): p. 012012, IOP Publishing, (2020). DOI: https://doi.org/10.1088/1757-899x/995/1/012012
  51. Casamayor-Pujol, V., Morenza-Cinos, M., Gastón, B., and Pous, R., “Autonomous stock counting based on a stigmergic algorithm for multi-robot systems”, Computers in Industry, 122: 103259, (2020). DOI: https://doi.org/10.1016/j.compind.2020.103259
  52. Van der Auweraer, S., and Boute, R., “Forecasting spare part demand using service maintenance information”, International Journal of Production Economics, 213: 138-149, (2019). DOI: https://doi.org/10.1016/j.ijpe.2019.03.015
  53. Frenk, J. B. G., Javadi, S., Pourakbar, M., and Sezer, S. O., “An exact static solution approach for the service parts end-of-life inventory problem”, European Journal of Operational Research, 272(2): 496-504, (2019). DOI: https://doi.org/10.1016/j.ejor.2018.06.041
  54. Keivanpour, S., and Kadi, D. A., “The effect of “Internet of things” on aircraft spare parts inventory Management”, IFAC-PapersOnLine, 52(13): 2343-2347, (2019). DOI: https://doi.org/10.1016/j.ifacol.2019.11.556
  55. Durán, O., Carrasco, A., Afonso, P. S., and Durán, P. A., “Evolutionary optimization of spare parts inventory policies: a life cycle costing perspective”, IFAC-PapersOnLine, 52(13): 2243-2248, (2019). DOI: https://doi.org/10.1016/j.ifacol.2019.11.539
  56. Zhang, C., Gao, W., Yang, T., and Guo, S., “Opportunistic maintenance strategy for wind turbines considering weather conditions and spare parts inventory management”, Renewable Energy, 133: 703-711, (2019). DOI: https://doi.org/10.1016/j.renene.2018.10.076
  57. Öztürk, F. S., “An integrated production scheduling and capacity planning for the maintenance and repair operations in airline industry with multiple types rotable inventory: A fix and optimize heuristic”, MSc. Thesis, TOBB University of Economics and Technology, (2018).
  58. Hwang, J. Q., and Samat, H. A., “A Review on Joint Optimization of Maintenance with Production Planning and Spare Part Inventory Management”, In Institute of Physics Conference Series: Materials Science and Engineering, 530(1): p. 012048. Institute of Physics Publishing, (2019). DOI: https://doi.org/10.1088/1757-899x/530/1/012048
  59. Prihandoyo, A. A., Zagloel, T. Y. M., and Ardi, R., “Integration Model of Stock Inventory with Multi-Echelon Logistic and Predictive Maintenance”, In Proceedings of the 4th International Conference on Industrial and Business Engineering, 41-47, (2018). DOI: https://doi.org/10.1145/3288155.3290588
  60. Somarin, A. R., Chen, S., Asian, S., and Wang, D. Z., “A heuristic stock allocation rule for repairable service parts”, International Journal of Production Economics, 184: 131-140, (2017). DOI: https://doi.org/10.1016/j.ijpe.2016.11.013
  61. Wild, T., “Best practice in inventory management”, Routledge, (2017).
  62. Nguyen, K. A., Do, P., and Grall, A., “Joint predictive maintenance and inventory strategy for multi-component systems using Birnbaum’s structural importance”, Reliability Engineering and System Safety, 168: 249-261, (2017). DOI: https://doi.org/10.1016/j.ress.2017.05.034
  63. Dinçer, S. E., and Ekin, E., “A solution approach to spare parts inventory management problems with linear programming in the aviation industry”, Journal of Life Economics, 4(2): 77-102, (2017).
  64. Poppe, J., Basten, R. J., Boute, R. N., and Lambrecht, M. R., “Numerical study of inventory management under various maintenance policies”, Reliability Engineering and System Safety, 168, 262-273, (2017). DOI: https://doi.org/10.1016/j.ress.2017.06.012
  65. Bounou, O., El Barkany, A., and El Biyaali, A., “Inventory models for spare parts management: a review”, In International Journal of Engineering Research in Africa, 28: 182-198, (2017). DOI: https://doi.org/10.4028/www.scientific.net/jera.28.182
  66. Durán, O., Macchi, M., and Roda, I., “On the relationship of spare parts inventory policies with Total Cost of Ownership of industrial assets”, International Federation of Automatic Control-PapersOnline, 49(28): 19-24, (2016). DOI: https://doi.org/10.1016/j.ifacol.2016.11.004
  67. Erkoç, M., and Ertogral, K., “Overhaul planning and exchange scheduling for maintenance services with rotable inventory and limited processing capacity”, Computers and Industrial Engineering, 98: 30-39, (2016). DOI: https://doi.org/10.1016/j.cie.2016.05.021
  68. Sleptchenko, A., and van der Heijden, M., “Joint optimization of redundancy level and spare part inventories”, Reliability Engineering and System Safety, 153: 64-74, (2016). DOI: https://doi.org/10.1016/j.ress.2016.04.006
  69. Bousdekis, A., Papageorgiou, N., Magoutas, B., Apostolou, D., and Mentzas, G., “A proactive event-driven decision model for joint equipment predictive maintenance and spare parts inventory optimization”, Procedia Collège International Pour la Recherche en Productique, 59: 184-189, (2017). DOI: https://doi.org/10.1016/j.procir.2016.09.015
  70. Gu, J., Zhang, G., and Li, K. W., “Efficient aircraft spare parts inventory management under demand uncertainty”, Journal of air transport management, 42: 101-109, (2015). DOI: https://doi.org/10.1016/j.jairtraman.2014.09.006
  71. Grondys, K., “Issues of Safety Stock Management of Spare Parts in Industrial Companies”, International Journal of Arts and Sciences, 8(4): 553, (2015).
  72. Rego, J. R., and De Mesquita, M. A., “Demand forecasting and inventory control: A simulation study on automotive spare parts”, International Journal of Production Economics, 161: 1-16, (2015). DOI: https://doi.org/10.1016/j.ijpe.2014.11.009
  73. Ronzoni, C., Ferrara, A., and Grassi, A., “A stochastic methodology for the optimal management of infrequent demand spare parts in the automotive industry”, International Federation of Automatic Control-PapersOnLine, 48(3): 1405-1410, (2015). DOI: https://doi.org/10.1016/j.ifacol.2015.06.283
  74. Hu, Q., Bai, Y., Zhao, J., and Cao, W., “Modeling spare parts demands forecast under two-dimensional preventive maintenance policy”, Mathematical Problems in Engineering, (2015). DOI: https://doi.org/10.1155/2015/728241
  75. Madan, A. K., and Ranganath, M. S., “Application of selective inventory control techniques for cutting tool inventory modeling and inventory reduction-A case study”, In International Conference of Advance Research and Innovation, 127: 135, (2014).
  76. Du Toit, D., “Decision-making framework for inventory management of spare parts in capital-intensive industries”, PhD. Thesis, Stellenbosch: Stellenbosch University, (2014).
  77. Bülbül, P., “An Integrated model for preventive maintenance and spare part inventory planning”, (MSc. Thesis, Middle East Technical University, (2014).
  78. Gupta, A., “Development of decision support system for optimal selection of inventory policy for India automotive industry”, National Institute of Technology Kurukshetra, (2014).
  79. Buyukkaramikli, N. C., van Ooijen, H. P., and Bertrand, J. W. M., “Integrating inventory control and capacity management at a maintenance service provider”, Annals of Operations Research, 231(1): 185-206, (2015). DOI: https://doi.org/10.1007/s10479-013-1506-1
  80. Van Horenbeek, A., Buré, J., Cattrysse, D., Pintelon, L., and Vansteenwegen, P., “Joint maintenance and inventory optimization systems: A review”, International Journal of Production Economics, 143(2): 499-508, (2013). DOI: https://doi.org/10.1016/j.ijpe.2012.04.001
  81. Bacchetti, A., and Saccani, N., “Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice”, Omega, 40(6): 722-737, (2012). DOI: https://doi.org/10.1016/j.omega.2011.06.008
  82. Krajčovič, M., and Plinta, D., “Comprehensive approach to the inventory control system improvement”, Management and Production Engineering Review, (2012).
  83. Afifi, S., Hrouga, M., Mjirda, A., and Allaoui, H., “A memetic based algorithm for simultaneous preventive maintenance scheduling and spare-parts inventory management for manufacturing systems”, Applied Soft Computing, 151: 111161, (2024). DOI: https://doi.org/10.1016/j.asoc.2023.111161
  84. Makarova, I., Buyvol, P., Gabsalikhova, L., Belyaev, E., and Mukhametdinov, E., “Decision Making under Conditions of Uncertainty and Risk in the Formation of Warehouse Stock of an Automotive Service Enterprise”, Algorithms, 16(8): 388, (2023). DOI: https://doi.org/10.3390/a16080388
  85. Scarf, P., Syntetos, A., and Teunter, R., “Joint maintenance and spare-parts inventory models: a review and discussion of practical stock-keeping rules”, IMA Journal of Management Mathematics, 35(1): 83-109, (2024). DOI: https://doi.org/10.1093/imaman/dpad020
  86. Dey, B. K., and Seok, H., “Intelligent inventory management with autonomation and service strategy”, Journal of Intelligent Manufacturing, 35(1): 307-330, (2024). DOI: https://doi.org/10.1007/s10845-022-02046-4
  87. Setiawan, W., Santosa, N., Winarto, F. E. W., and Mandala, W. W., “Inventory Management and Proactive Maintenance to Enhance Operational Efficiency in Excavators: Focus on Common Spare Parts Issues”, Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa and Inovasi, 49-58, (2025). DOI: https://doi.org/10.35814/asiimetrik.v7i1.7770
  88. Tang, J., Deng, Q., Wang, C., Liao, M., and Han, W., “Integrated optimization of maintenance, spare parts management and operation for a multi-component system: A case study”, Computers and Industrial Engineering, 110942, (2025). DOI: https://doi.org/10.1016/j.cie.2025.110942
  89. Zhang, B., Hu, C., Zheng, J., and Pei, H., “Maintenance Decision-Making Using Intelligent Prognostics Within a Single Spare Parts Support System”, Sensors, 25(3): 837, (2025). DOI: https://doi.org/10.3390/s25030837
  90. Langevin, A., and Riopel, D., “Logistics systems: design and optimization”, 2, Springer Science and Business Media, (2005).
  91. Roodbergen, K. J., and Koster, R., “Routing methods for warehouses with multiple cross aisles”, International Journal of Production Research, 39(9): 1865-1883, (2001). DOI: https://doi.org/10.1080/00207540110028128
  92. Apsalons, R., and Gromov, G., “Using the min/max method for replenishment of picking locations”, Transport and Telecommunication, 18(1): 79, (2017). DOI: https://doi.org/10.1515/ttj-2017-0008
  93. Frazelle, E. H., “World-class warehousing and material handling”, McGraw-Hill Education, (2002).
  94. Ertek, G., “Storage Systems, International Logistics”, Ed: B. Çatay and G. Öztürk, Anadolu University Publications- No: 2625, Eskişehir, 190, (2012).
  95. Chen, P. S., Huang, C. Y., Yu, C. C., and Hung, C. C., “The examination of key performance indicators of warehouse operation systems based on detailed case studies”, Journal of Information and Optimization Sciences, 38(2): 367-389, (2017). DOI: https://doi.org/10.1080/02522667.2016.1224465
  96. Ribino, P., Cossentino, M., Lodato, C., and Lopes, S., “Agent-based simulation study for improving logistic warehouse performance”, Journal of Simulation, 12(1): 23-41,(2018). DOI: https://doi.org/10.1057/s41273-017-0055
  97. Kayakutlu, G., and Büyüközkan, G., “Assessing performance factors for a 3PL in a value chain”, International Journal of Production Economics, 131(2): 441-452, (2011). DOI: https://doi.org/10.1016/j.ijpe.2010.12.019
  98. He, Z., Chen, P., Liu, H., and Guo, Z., “Performance measurement system and strategies for developing low-carbon logistics: A case study in China”, Journal of Cleaner Production, 156: 395-405, (2017). DOI: https://doi.org/10.1016/j.jclepro.2017.04.071
  99. Nikolaou, I. E., Evangelinos, K. I., and Allan, S., “A reverse logistics social responsibility evaluation framework based on the triple bottom line approach”, Journal of Cleaner Production, 56: 173-184, (2013). DOI: https://doi.org/10.1016/j.jclepro.2011.12.009
  100. Limère, V., “To kit or not to kit: optimizing part feeding in the automotive assembly industry”, PhD. Thesis, Ghent University, (2011).
  101. Albert, P. W., Rönnqvist, M., and Lehoux, N., “Heterogeneous products allocation in a warehouse–case study in the automobile industry”, Journal of Industrial and Production Engineering, 1-20, (2025). DOI: https://doi.org/10.1080/21681015.2025.2498661
  102. Tian, M., “Optimization of Storage Space of Multi Variety and Small Batch Automobile Parts Stereoscopic Warehouse”, International Conference on Distributed Computing and Optimization Techniques, 1-5, (2024). DOI: https://doi.org/10.1109/icdcot61034.2024.10516015
  103. Caridade, R., Pereira, T., Ferreira, L. P., and Silva, F. J. G., “Analysis and optimisation of a logistic warehouse in the automotive industry”, Procedia Manufacturing, 13: 1096-1103, (2017). DOI: https://doi.org/10.1016/j.promfg.2017.09.170
  104. Sayin, A. A., and Maden, M., “The Effect of Warehouse Design Activities on Operational Efficiency in Automotive Spare Parts Company”, Eurasian Journal of Researches in Social and Economics, 7(2): 91-109, (2020).
  105. Hernández-Rodríguez, S., Hernández-Lira, C. A., Aguilar-Rico, A., Flores-Becerra, G., Flores-Méndez, J., and Vázquez-Cuchillo, O., “A recommender system applied to the indirect materials selection process (RS-IMSP) for producing automobile spare parts”, Computers in Industry, 82: 233-244, (2016). DOI: https://doi.org/10.1016/j.compind.2016.07.004
  106. Torabizadeh, M., Yusof, N. M., Ma’aram, A., and Shaharoun, A. M., “Identifying sustainable warehouse management system indicators and proposing new weighting method”, Journal of Cleaner Production, 248: 119190, (2020). DOI: https://doi.org/10.1016/j.jclepro.2019.119190
  107. Saueressig, G. G., de Paris, A., Bauer, J. M., Luchese, J., Sellitto, M. A., and Antunes Jr, J. A. V., “Strategic materials positioning matrix: An application in the automotive industry in Southern Brazil”, International Journal of Industrial Engineering and Management, 8(2): 77, (2017). DOI: https://doi.org/10.24867/ijiem-2017-2-109
  108. Maryadi, D., Moulita, R. N., King, M. L., Veranika, R. M., and Madagaskar, M., “Value Stream Mapping for Warehouse Process in Automotive Manufacturing Case”, International Journal of Mechanical Computational and Manufacturing Research, 13(3): 89-97, (2024).
  109. Freitas, A. M., Silva, F. J. G., Ferreira, L. P., Sá, J. C., Pereira, M. T., and Pereira, J., “Improving efficiency in a hybrid warehouse: a case study”, Procedia Manufacturing, 38: 1074-1084, (2019). DOI: https://doi.org/10.1016/j.promfg.2020.01.195
  110. Moussa, F. Z. B., De Guio, R., Dubois, S., Rasovska, I., and Benmoussa, R., “Study of an innovative method based on complementarity between ARIZ, lean management and discrete event simulation for solving warehousing problems”, Computers and Industrial Engineering, 132: 124-140, (2019). DOI: https://doi.org/10.1016/j.cie.2019.04.024
  111. Schindlerová, V., Šajdlerová, I., and Zmeškal, P., “Implementation of the Principles of TPM in Field of Maintenance Preparations”, Transactions of the VŠB - Technical University of Ostrava, Mechanical Series, 62 (1): 51–57, (2016). DOI: https://doi.org/10.22223/tr.2016-1/2010
  112. Meneses Ramos, R. D., and Suarez Azabache, D. G., “A proposal for a machine control plan using the Total Productive Maintenance (TPM) methodology in the comprehensive warehouses of SMEs in the construction industry in the province of Arequipa”, Bachelor Thesis, Peruvian University of Applied Sciences, (2022).
  113. Boissie, K., Addouche, S. A., Zolghadri, M., and Richard, D., “Obsolescence Mitigation in Automotive Industry using Long Term Storage Feasibility Model”, Procedia Manufacturing, 16: 39-46, (2018). DOI: https://doi.org/10.1016/j.promfg.2018.10.156
  114. Sufa, M. F., and Mulyana, M. K., “Spare Part Warehouse Management Analysis Using 5S Approach and FIFO System”, In Proceeding of International Conference on Science, Health, And Technology, 318-322, (2021).
  115. Chlebus, E., Helman, J., Olejarczyk, M., and Rosienkiewicz, M., “A new approach on implementing TPM in a mine-A case study”, Archives of Civil and Mechanical Engineering, 15(4): 873-884, (2015). DOI: https://doi.org/10.1016/j.acme.2015.07.002
  116. Nevliudov, I., Yevsieiev, V., Klymenko, O., Demska, N., and Vzhesnievskyi, M., “Evolutions of Group Management Development of Mobile Robotic Platforms in Warehousıng 4.0”, Innovative Technologies and Scientific Solutions for Industries, 4(18): 57-64, (2021). DOI: https://doi.org/10.30837/itssi.2021.18.057
  117. Korkusuz Polat, T., and Baran, E., “A Blockchain-Based Quality 4.0 Application for Warehouse Management System”, Applied Sciences, 14(23): 10950, (2024). DOI: https://doi.org/10.3390/app142310950
  118. Işik, E. and Antmen, Z. F., “Multiple Criteria Decision Making Approaches for The Proposal of Warehouse: An Automotive Operation Application”, Cukurova University Journal of Science and Engineering Sciences, 39: 22-31, (2020).
  119. Arslan, M., “Use of decision support systems in warehouse management and an application on determining ımportant criteria for product placement”, MSc. Thesis, Maltepe University, Institute of Social Sciences, (2019).
  120. Boysen, N., Emde, S., Hoeck, M., and Kauderer, M., “Part logistics in the automotive industry: Decision problems, literature review and research agenda”, European Journal of Operational Research, 242(1): 107-120, (2015). DOI: https://doi.org/10.1016/j.ejor.2014.09.065
  121. Miralam, M., “Impact of implementing warehouse management system on auto spare part industry market in Saudi Arabia”, Review of Integrative Business and Economics Research, 6(3): 56, (2017).
  122. Škerlič, S., Muha, R., and Sokolovskij, E., “Application of modern warehouse technology in the Slovenian automotive industry”, Transport, 32(4): 415-425, (2017). DOI: https://doi.org/10.3846/16484142.2017.1354315
  123. Udeh, D. O., and Karaduman, I., “The impact of supply chain in the warehouse management systems of Turkish automotive industry”, International Journal of Economics, Commerce and Management, 3(5): 410-423, (2015).
  124. Kučera, T., “Application of the activity-based costing to the logistics cost calculation for warehousing in the automotive industry”, Komunikácie: Communications (Scientific Letters of the University of Žilina), 21: 4, (2019). DOI: https://doi.org/10.26552/com.c.2019.4.35-42
  125. Glock, C. H., and Grosse, E. H., “Storage policies and order picking strategies in U-shaped order-picking systems with a movable base”, International Journal of Production Research, 50(16): 4344-4357, (2012). DOI: https://doi.org/10.1080/00207543.2011.588621
  126. Boysen, N., Schwerdfeger, S., and Stephan, K., “A review of synchronization problems in parts-to-picker warehouses”, European Journal of Operational Research, (2022). DOI: https://doi.org/10.1016/j.ejor.2022.09.035
  127. Gül, G., Erol, B., Öngelen, G., Eser, S., Çetinkaya, Ç., Özmutlu, H. C., and Erhuy, C. G., “Maximization of Warehouse Storage”, Industrial Engineering, 27(4): 26-38, (2016).
  128. Kumar, D., Singh, R. K., Mishra, R., and Wamba, S. F., “Applications of the internet of things for optimizing warehousing and logistics operations: a systematic literature review and future research directions”, Computers and Industrial Engineering, 108455, (2022). DOI: https://doi.org/10.1016/j.cie.2022.108455
  129. Accorsi, R., Manzini, R., and Maranesi, F., “A decision-support system for the design and management of warehousing systems”, Computers in Industry, 65(1): 175-186, (2014). DOI: https://doi.org/10.1016/j.compind.2013.08.007
  130. Dui, H., Yang, X., and Liu, M., “Importance measure-based maintenance analysis and spare parts storage configuration in two-echelon maintenance and supply support system”, International Journal of Production Research, 1-18, (2022). DOI: https://doi.org/10.1080/00207543.2022.2142312
  131. Wijaya, E., “Layout Analysis of Goods Storage: Case Study Spare Part Warehouse Z Company”, Jurnal Rekayasa Sistem Industri, 11(1): 47-56, (2022). DOI: https://doi.org/10.26593/jrsi.v11i1.5139.47-56
  132. Malkin, V. S., Kravtsova, E. A., Turbin, I. V., and Popova, L. I., “Creation of optimal warehouse of spare parts with minimum cost and maximum fail-safety”, In IOP Conference Series: Materials Science and Engineering, 632(1): p. 012076, Institute of Physics Publishing, (2019). DOI: https://doi.org/10.1088/1757-899x/632/1/012076
  133. Lucero-Flores, M. A., Sánchez-Partida, D., Cano-Olivos, P., and Cuautle-Gutierrez, L., “Control and Continuous Improvement in the Picking Area”, Proceedings of the International Conference on Industrial Engineering and Operations Management Monterrey, Mexico, (2021).
  134. Öztürk, F. S., “An integrated production scheduling and capacity planning for the maintenance and repair operations in airline industry with multiple types rotable inventory: A fix and optimize heuristic”, MSc. Thesis, TOBB University of Economics and Technology, (2018).