Open Access Research Article

Opportunistic Maintenance Modeling in a Closed-Loop Supply Chain: The Impact of Spare Parts Material, Technician Skill, and Environmental Conditions

Authors

  • Mahnam Najafi * Department of Industrial Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran.
  • Hiva Faroughi Department of Industrial Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran.

https://doi.org/10.48313/scodm.v2i4.47

Abstract

Opportunistic Maintenance (OM) is one of the key approaches for optimizing maintenance operations in Closed-Loop Supply Chains (CLSC), which leverages the repair and recovery of spare parts to reduce costs and improve reliability. In this paper, a new OM model is proposed that, in addition to classical factors such as component age and economic and structural dependencies, incorporates spare-part material type, technician skill level, and environmental conditions into maintenance decision-making. The material of spare parts directly affects their failure rate and service life, while technician skill enhances repair quality and post-repair lifetime. Moreover, environmental conditions such as temperature and humidity alter the degradation rate of components. Preliminary results and conceptual analyses indicate that the proposed model can reduce costs, improve the overall performance of the closed-loop supply chain, and enhance the reliability of repaired components.

Keywords

Opportunistic maintenance Spare parts Structural dependency Closed-loop supply chain Reliability
References (32)
  1. [1] Jahangiri, S., Abolghasemian, M., Pourghader Chobar, A., Nadaffard, A., & Mottaghi, V. (2021). Ranking of key resources in the humanitarian supply chain in the emergency department of iranian hospital: A real case study in covid-19 conditions. Journal of applied research on industrial engineering, 8(Special Issue), 1–10. https://doi.org/10.22105/jarie.2021.275255.1263

  2. [2] Abolghasemian, M., Pourghader Chobar, A., Vaseei, M., & Nasiri Jan Agha, M. R. (2024). Mathematical modeling to evaluate knowledge management in the development of industrial clusters. International journal of applied operational research-an open access journal, 12(4), 1–18. http://dx.doi.org/10.71885/ijorlu-2024-1-677

  3. [3] Agrawal, V. V, Atasu, A., & Van Wassenhove, L. N. (2019). OM forum—new opportunities for operations management research in sustainability. Manufacturing & service operations management, 21(1), 1–12. https://doi.org/10.1287/msom.2017.0699

  4. [4] Kerin, M., & Pham, D. T. (2020). Smart remanufacturing: A review and research framework. Journal of manufacturing technology management, 31(6), 1205–1235. https://doi.org/10.1108/JMTM-06-2019-0205

  5. [5] Liu, C., Zhu, Q., Wei, F., Rao, W., Liu, J., Hu, J., & Cai, W. (2019). A review on remanufacturing assembly management and technology. The international journal of advanced manufacturing technology, 105(11), 4797–4808. https://doi.org/10.1007/s00170-019-04617-x%0A%0A

Article Metrics

How to Cite

Najafi, M. ., & Faroughi, H. . (2025). Opportunistic Maintenance Modeling in a Closed-Loop Supply Chain: The Impact of Spare Parts Material, Technician Skill, and Environmental Conditions. Supply Chain and Operations Decision Making, 2(4), 243-260. https://doi.org/10.48313/scodm.v2i4.47

Similar Articles

1-10 of 49

You may also start an advanced similarity search for this article.