Analyzing the impact of sustainability on the network design and planning decisions in a spare part supply chain: an empirical investigation.

Document Type : Research Paper

Authors

1 Department of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

Abstract

Economical, environmental, and social issues are significant challenges for industries and governments nowadays. The spare parts impose high inventory costs on the companies and require human resources, energy, and budget for the repair operations. These issues justify integrating repair, and inventory management decisions to reduce costs. Since the system is interacting with the environment, incorporating the sustainability dimensions with network design and planning decisions help managers to make more reliable decisions. We investigated the social and environmental dimensions to cover the sustainability dimensions of the spare part supply chain. These attributes contribute to industry-oriented properties in real-world problems. This paper investigates a multi-objective model to minimize costs while maximizing sustainability in a repairable spare part supply chain. Life cycle assessment (LCA) is utilized to assess social and environmental dimensions. Finally, the model is solved using NSGA-II with a priority-based encoding and decoding procedure. The findings shed light on contributing to formulating the spare part supply chain sustainability which integrates the network design and planning decisions resulting in more reliable outcomes.

Keywords

Main Subjects

References

Agrawal, S., Singh, R. K., & Murtaza, Q. (2015). A literature review and perspectives in reverse logistics. Resources, Conservation and Recycling, 97, 76–92.
Aliakbar Hasani, S. H. H. (2014). A comprehensive bi-objective model  for reverse supply chain design under uncertainty: A memetic algorithm. Industrial Management Vision, 16, Article 16. http://ensani.ir/fa/article/397269
Aras, N., Aksen, D., & Tanuğur, A. G. (2008). Locating collection centers for incentive-dependent returns under a pick-up policy with capacitated vehicles. European Journal of Operational Research, 191(3), 1223–1240.
Babaveisi, V., Teimoury, E., Gholamian, M. R., & Rostami-Tabar, B. (2022). Integrated demand forecasting and planning model for repairable spare part: An empirical investigation. International Journal of Production Research, 1–17. https://doi.org/10.1080/00207543.2022.2137596
Batista, L., Bourlakis, M., Smart, P., & Maull, R. (2018). In search of a circular supply chain archetype–a content-analysis-based literature review. Production Planning & Control, 29(6), 438–451.
Carrasco-Gallego, R., Ponce-Cueto, E., & Dekker, R. (2012). Closed-loop supply chains of reusable articles: A typology grounded on case studies. International Journal of Production Research, 50(19), 5582–5596.
Choudhary, A., Sarkar, S., Settur, S., & Tiwari, M. K. (2015). A carbon market sensitive optimization model for integrated forward–reverse logistics. International Journal of Production Economics, 164, 433–444.
den Boer, J., Lambrechts, W., & Krikke, H. (2020). Additive manufacturing in military and humanitarian missions: Advantages and challenges in the spare parts supply chain. Journal of Cleaner Production, 257, 120301.
Digiesi, S., Mossa, G., & Rubino, S. (2014). A sustainable EOQ model for repairable spare parts under uncertain demand. IMA Journal of Management Mathematics, 26(2), Article 2. https://doi.org/10.1093/imaman/dpu004
Doan, L. T. T., Amer, Y., Lee, S.-H., Phuc, P. N. K., & Dat, L. Q. (2019). A comprehensive reverse supply chain model using an interactive fuzzy approach – A case study on the Vietnamese electronics industry. Applied Mathematical Modelling, 76, 87–108. https://doi.org/10.1016/j.apm.2019.06.003
Driessen, M. A. (2018). Integrated capacity planning and inventory control for repairable spare parts.
Farrokh, M., Azar, A., & Jandaghi, G. (2016). A robust-fuzzy programming approach for a closed-loop supply chain design. 6, 9–43.
Fathollahi-Fard, A. M., Ahmadi, A., & Al-e-Hashem, S. M. J. M. (2020). Sustainable closed-loop supply chain network for an integrated water supply and wastewater collection system under uncertainty. Journal of Environmental Management, 275, 111277. https://doi.org/10.1016/j.jenvman.2020.111277
Fathollahi-Fard, A. M., & Hajiaghaei-Keshteli, M. (2018). A stochastic multi-objective model for a closed-loop supply chain with environmental considerations. Applied Soft Computing, 69, 232–249. https://doi.org/10.1016/j.asoc.2018.04.055
Finkbeiner, M. (2011). Towards life cycle sustainability management. Springer, Dordrecht/ Heidelberg/London/New York.
Fonseca, M. C., García-Sánchez, Á., Ortega-Mier, M., & Saldanha-da-Gama, F. (2010). A stochastic bi-objective location model for strategic reverse logistics. Top, 18(1), 158–184.
Frandsen, C. S., Nielsen, M. M., Chaudhuri, A., Jayaram, J., & Govindan, K. (2020). In search for classification and selection of spare parts suitable for additive manufacturing: A literature review. International Journal of Production Research, 58(4), 970–996. https://doi.org/10.1080/00207543.2019.1605226
Gholamian, M. R., & Heydari, M. (2017). An inventory model with METRIC approach in location-routing-inventory problem. ADVANCES IN PRODUCTION ENGINEERING & MANAGEMENT, 12(2), Article 2. https://doi.org/10.14743/apem2017.2.244
González-Varona, J. M., Poza, D., Acebes, F., Villafáñez, F., Pajares, J., & López-Paredes, A. (2020). New Business Models for Sustainable Spare Parts Logistics: A Case Study. Sustainability, 12(8), 3071.
Hatefi, S. M., Jolai, F., Torabi, S. A., & Tavakkoli-Moghaddam, R. (2015). Reliable design of an integrated forward-revere logistics network under uncertainty and facility disruptions: A fuzzy possibilistic programing model. KSCE Journal of Civil Engineering, 19(4), 1117–1128.
Hora, M. E. (1987). The unglamorous game of managing maintenance. Business Horizons, 30(3), 67–75.
Jayaram, J., & Avittathur, B. (2015). Green supply chains: A perspective from an emerging economy. International Journal of Production Economics, 164, 234–244.
Jensen, A. (2001). A bridge to sustainable products. 1st International Conference of Life Cycle Management (LCM). Dk-TEKNIK ENERGY & ENVIRONMENT, Copenhagen/Soeborg, 27–28.
Kim, J., Chung, B. D., Kang, Y., & Jeong, B. (2018). Robust optimization model for closed-loop supply chain planning under reverse logistics flow and demand uncertainty. Journal of Cleaner Production, 196, 1314–1328. https://doi.org/10.1016/j.jclepro.2018.06.157
Kosanoglu, F., Turan, H. H., & Atmis, M. (2018). A Simulated Annealing Algorithm for Integrated Decisions on Spare Part Inventories and Cross-Training Policies in Repairable Inventory Systems. Proceedings of International Conference on Computers and Industrial Engineering, 1–14.
Koskela, S., Dahlbo, H., Judl, J., Korhonen, M.-R., & Niininen, M. (2014). Reusable plastic crate or recyclable cardboard box? A comparison of two delivery systems. Journal of Cleaner Production, 69, 83–90. https://doi.org/10.1016/j.jclepro.2014.01.045
Moradgholi, M., Paydar, M. M., Mahdavi, I., & Jouzdani, J. (2016). A genetic algorithm for a bi-objective mathematical model for dynamic virtual cell formation problem. Journal of Industrial Engineering International, 12(3), 343–359.
Pauliuk, S., Kondo, Y., Nakamura, S., & Nakajima, K. (2017). Regional distribution and losses of end-of-life steel throughout multiple product life cycles—Insights from the global multiregional MaTrace model. Resources, Conservation and Recycling, 116, 84–93.
Rashidi Komijan, A., Lotfi, M. R., & Naghavi, S. M. (2015). An integerated forward-reverse supply chain considering location and transportation policies (No. 2). 26(2), Article 2.
Schulze, S., & Weckenborg, S. (2012). Improving Forecasts for a Higher Sustainability in Spare Parts Logistics. In Sustainable Manufacturing (pp. 243–247). Springer.
Shih, L.-H. (2001). Reverse logistics system planning for recycling electrical appliances and computers in Taiwan. Resources, Conservation and Recycling, 32(1), 55–72. https://doi.org/10.1016/S0921-3449(00)00098-7
Torabi, S. A., & Sharafat, M. R. (2013). Designing a sustainable supply chain under uncertainty: Oil industry. 10th International Industrial Engineering Conference. https://www.tpbin.com/article/13079
Turan, H. H., Sleptchenko, A., Pokharel, S., & ElMekkawy, T. Y. (2018). A clustering-based repair shop design for repairable spare part supply systems. Computers and Industrial Engineering. https://doi.org/10.1016/j.cie.2018.08.032
Wingerden, E. van, Tan, T., & Houtum, G. J. V. (2019). The impact of an emergency warehouse in a two-echelon spare parts network. European Journal of Operational Research, 276(3), Article 3. https://doi.org/10.1016/j.ejor.2019.01.068
Zarbakhshnia, N., Soleimani, H., Goh, M., & Razavi, S. S. (2019). A novel multi-objective model for green forward and reverse logistics network design. Journal of Cleaner Production, 208, 1304–1316. https://doi.org/10.1016/j.jclepro.2018.10.138
Zhao, Y., Shi, Y., & Karimi, H. R. (2012). Entry-item-quantity-ABC analysis-based multitype cigarette fast sorting system. Mathematical Problems in Engineering, 2012.

Files

History

  • Receive Date: 05 January 2023
  • Revise Date: 21 April 2023
  • Accept Date: 18 June 2023

Share

How to cite

Statistics