Reabastecimiento conjunto para la gestión de inventarios de partes de repuesto: caso de estudio
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oct 6, 2025
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https://doi.org/10.36677/rici.v3i3.26602
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Victor Sánchez-Guzmán
http://orcid.org/0009-0005-4415-1497
Lourdes Loza-Hernández
http://orcid.org/0000-0001-5107-7110
Agustín Bustos-Rosales
http://orcid.org/0000-0001-5074-0355
Sergio Vázquez-Aranda
http://orcid.org/0009-0007-7073-6557
http://orcid.org/0009-0005-4415-1497
Lourdes Loza-Hernández
http://orcid.org/0000-0001-5107-7110
Agustín Bustos-Rosales
http://orcid.org/0000-0001-5074-0355
Sergio Vázquez-Aranda
http://orcid.org/0009-0007-7073-6557
Resumen
En el sector automotriz, específicamente en la rama de autopartes, equilibrar los costos y la disponibilidad de productos es una tarea compleja. El objetivo de este trabajo es proponer una política de inventario que minimice los costos totales de inventario y satisfaga la demanda de los clientes de una empresa de autopartes en México, además de mostrar soluciones alternativas a los problemas derivados de la falta de una gestión adecuada de inventarios. Para lograr este objetivo, propone una metodología para facilitar la puesta en práctica de los tomadores de decisiones, se realizó un análisis de las autopartes para seleccionar las de mayor interés para la empresa y pronosticar su demanda mediante modelos ARIMA. Posteriormente, se compararon las políticas de inventario para la revisión periódica y continua de dichos productos. Finalmente, se aplicó el sistema de reabastecimiento conjunto propuesto por Atkins e Iyogun a la mejor política que permite la existencia de faltantes y la ausencia de faltantes, logrando que los artículos con baja demanda se incluyan en los pedidos de artículos con alta rotación. Los resultados indican que la mejor política de inventario a aplicar en la compañía en la política de revisión continua.
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SÁNCHEZ-GUZMÁN, Victor et al.
Reabastecimiento conjunto para la gestión de inventarios de partes de repuesto: caso de estudio.
Ideas en Ciencias de la Ingeniería, [S.l.], v. 3, n. 3, p. 55-72, oct. 2025.
ISSN 2992-7447.
Disponible en: <https://ideasencienciasingenieria.uaemex.mx/article/view/26602>. Fecha de acceso: 26 ago. 2026
doi: https://doi.org/10.36677/rici.v3i3.26602.
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Esta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial-SinObrasDerivadas 4.0.
Citas
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[22] P. Samouei et al., “A network approach modeling of multi-echelon spare-part inventory system with backorders and quantity discount,” Annals of Operations Research, vol. 226, pp. 551–563, 2015, doi: 10.1007/s10479-014-1718-z.
[23] L. A. San-José et al., “Profit maximization in an inventory system with time-varying demand, partial backordering and discrete inventory cycle,” Annals of Operations Research, 2021, doi: 10.1007/s10479-021-04161-6.
[24] S. Poormoaied, “Inventory decision in a periodic review inventory model with two complementary products,” Annals of Operations Research, 2021, doi: 10.1007/s10479-021-03949-w.
[25] M. Varas, F. Basso, and A. Lüer-Villagra, “Managing premium wines using an (s−1, s) inventory policy: A heuristic solution approach,” Annals of Operations Research, vol. 280, pp. 351–376, 2019, doi: 10.1007/s10479-019-03266-3.
[26] B. Roushdy, N. Sobhy, A. Abdelhamid, and A. Mahmoud, “Inventory Control for a Joint Replenishment Problem with Stochastic Demand,” International Journal of Industrial and Manufacturing Engineering, vol. 5, no. 4, pp. 873–877, 2011.
[27] N. Salari and V. Makis, “Joint maintenance and just-in-time spare parts provisioning policy for a multi-unit production system,” Annals of Operations Research, vol. 287, pp. 351–377, 2020, doi: 10.1007/s10479-019-03371-3.
[28] E. Montes de Oca-Sánchez and L. Loza-Hernández, “Comparativo de métodos de pronóstico en series de tiempo para la demanda de repuestos automotrices,” Investigación y Ciencia de la Universidad Autónoma de Aguascalientes, vol. 33, no. 94, e545, 2025, doi: 10.33064/iycuaa2025945451.
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[30] T.S. Winter, J.H. van Vuuren, “A Practical Method for Joint Inventory Replenishment under Supplier Constraints”. South African Journal of Industrial Engineering, vol.36 n.2. 2025. doi.org/10.7166/36-2-3194
[2] S. Nahmias and T. L. Olsen, Production and Operations Analysis. Long Grove, IL, USA: Waveland Press, Inc., 2015.
[3] E. A. Silver, D. F. Pyke, and R. Peterson, Inventory and Production Management in Supply Chains. Boca Raton, FL, USA: CRC Press, 2017.
[4] S. Axsäter, Inventory Control, International Series in Operations Research & Management Science. Cham, Switzerland: Springer, 2015.
[5] S. Makridakis and S. C. Wheelwright, Métodos de pronósticos. México, D.F.: Limusa, 2009.
[6] D. Atkins and P. Iyogun, “Periodic versus ‘can-order’ policies for coordinated multi-item inventory systems,” Management Science, vol. 34, no. 6, pp. 791–796, Jun. 1988.
[7] X. Ma, R. Rossi, and T. Archibald, “Stochastic Inventory Control: A Literature Review,” IFAC PapersOnLine, vol. 52, no. 13, pp. 1490–1495, Nov. 2019, doi: 10.1016/j.ifacol.2019.11.410.
[8] M. A. Bushuev, A. Guiffrida, M. Y. Jaber, and M. Khan, “A review of inventory lot sizing review papers,” Management Research Review, vol. 38, no. 3, pp. 283–298, 2015, doi: 10.1108/MRR-09-2013-0204.
[9] R. H. Ballou, Business Logistic Management, 5th ed. Upper Saddle River, NJ, USA: Prentice-Hall, 2003.
[10] R. A. Davis, Demand-Driven Inventory Optimization and Replenishment: Creating a More Efficient Supply Chain, 2nd ed. Hoboken, NJ, USA: Wiley, 2016.
[11] A. Kimms, Multi-Level Lot Sizing and Scheduling: Methods for Capacitated, Dynamic, and Deterministic Models (Production and Logistics). Heidelberg, Germany: Physica-Verlag HD, 1996.
[12] V. Suhandi and P.-S. Chen, “Joint Replenishment Dealing with Various Inventory Policies,” in Proc. 13th Annu. Int. Conf. Industrial Engineering and Operations Management, 2023, doi: 10.46254/AN13.20230083.
[13] A. R. Ravindran and J. D. P. Warsing, Supply Chain Engineering: Models and Applications. Boca Raton, FL, USA: CRC Press, 2013.
[14] I. T. Christou, Quantitative Methods in Supply Chain Management: Models and Algorithms. Berlin, Germany: Springer, 2013.
[15] R. Ramya, C. Rajendran, H. Ziegler, S. Mohapatra, and K. Ganesh, Capacitated Lot Sizing Problems in Process Industries. Cham, Switzerland: Springer, 2019.
[16] M. Hajiaghaei-Keshteli, S. M. Sajadifar, and R. Haji, “Determination of the economic policy of a three-echelon inventory system with (R, Q) ordering policy and information sharing,” Int. J. Adv. Manuf. Technol., vol. 55, pp. 831–841, 2011, doi: 10.1007/s00170-010-3112-6.
[17] E. Porteus, Foundations of Stochastic Inventory Theory. Stanford, CA, USA: Stanford Business Books, 2002.
[18] M. Xiang, R. Rossi, B. Martin-Barragán, and S. A. Tarim, “Computing non-stationary (s, S) policies using mixed integer linear programming,” European Journal of Operational Research, vol. 271, no. 2, pp. 490–500, 2018, doi: 10.1016/j.ejor.2018.05.030.
[19] L. Janssen, T. Claus, and J. Sauer, “Literature review of deteriorating inventory models by key topics from 2012 to 2015,” International Journal of Production Economics, vol. 182, pp. 86–112, Oct. 2016, doi: 10.1016/j.ijpe.2016.08.019.
[20] R. Kian, Ü. Gürler, and E. Berk, “The dynamic lot-sizing problem with convex economic production costs and setups,” International Journal of Production Economics, vol. 155, pp. 361–379, Oct. 2014, doi: 10.1016/j.ijpe.2014.02.006.
[21] I. Karakayali et al., “Capacitated replenishment and disposal planning for multiple products with resalable returns,” Annals of Operations Research, vol. 203, no. 1, pp. 325–350, Sep. 2013, doi: 10.1007/s10479-012-1112-7.
[22] P. Samouei et al., “A network approach modeling of multi-echelon spare-part inventory system with backorders and quantity discount,” Annals of Operations Research, vol. 226, pp. 551–563, 2015, doi: 10.1007/s10479-014-1718-z.
[23] L. A. San-José et al., “Profit maximization in an inventory system with time-varying demand, partial backordering and discrete inventory cycle,” Annals of Operations Research, 2021, doi: 10.1007/s10479-021-04161-6.
[24] S. Poormoaied, “Inventory decision in a periodic review inventory model with two complementary products,” Annals of Operations Research, 2021, doi: 10.1007/s10479-021-03949-w.
[25] M. Varas, F. Basso, and A. Lüer-Villagra, “Managing premium wines using an (s−1, s) inventory policy: A heuristic solution approach,” Annals of Operations Research, vol. 280, pp. 351–376, 2019, doi: 10.1007/s10479-019-03266-3.
[26] B. Roushdy, N. Sobhy, A. Abdelhamid, and A. Mahmoud, “Inventory Control for a Joint Replenishment Problem with Stochastic Demand,” International Journal of Industrial and Manufacturing Engineering, vol. 5, no. 4, pp. 873–877, 2011.
[27] N. Salari and V. Makis, “Joint maintenance and just-in-time spare parts provisioning policy for a multi-unit production system,” Annals of Operations Research, vol. 287, pp. 351–377, 2020, doi: 10.1007/s10479-019-03371-3.
[28] E. Montes de Oca-Sánchez and L. Loza-Hernández, “Comparativo de métodos de pronóstico en series de tiempo para la demanda de repuestos automotrices,” Investigación y Ciencia de la Universidad Autónoma de Aguascalientes, vol. 33, no. 94, e545, 2025, doi: 10.33064/iycuaa2025945451.
[29] E. M. Alvarez, M. C. Van der Heijden, and W. H. M. Zijm, “Service differentiation in spare parts supply through dedicated stocks,” Annals of Operations Research, vol. 231, no. 1, pp. 283–303, 2015, doi: 10.1016/j.ijpe.2012.02.019.
[30] T.S. Winter, J.H. van Vuuren, “A Practical Method for Joint Inventory Replenishment under Supplier Constraints”. South African Journal of Industrial Engineering, vol.36 n.2. 2025. doi.org/10.7166/36-2-3194