Optimization in Supply Chain Design of Assembled Products: A Case Study of HEPCO Company

Document Type : Research Paper

Authors

1 Assistant Professor, Department of Mechanical Engineering, Arak University of Technology, Arak, Iran

2 Associate Professor, Department of Industrial Engineering, Arak branch, Islamic Azad University, Arak, Iran

3 PhD Student, Department of Industrial Engineering, North Tehran branch, Islamic Azad University, Tehran, Iran

Abstract

HEPCO is an Iranian corporation that manufactures construction equipment and holds a supply chain with a traditional, non-integrated approach. The materials come from four different sources, including an engineering and parts company, domestic vendors, international vendors, and the company itself supplying the materials and components needed for assembling of products and delivering to customers. Having a non-integrated supply chain has led to an increase in total cost. Therefore, in order to reduce supply chain cost in this company, a three-level model including suppliers, manufacturers, and customers was used. Different ways also were applied to minimize chain cost, including purchase cost, transportation cost, inventory cost, assembly cost, and shortage cost, based on an integer linear mathematical model. It also considered such constraints as balance inventory, assembly capacity, storage capacity, amount of safety stock, and shortage, which were solved by MATLAB software. The results of proposed model were compared with the actual amount of variables in the study period, which indicated a significant reduction in the cost of proposed model comapred to the conventional methods.

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References

Abdolazimi, O., Shishebori, D., Goodarzian, F., Ghasemi, P., & Appolloni, A. (2021). Designing a new   mathematical model based on ABC analysis for inventory control problem: A real case study. RAIRO-Operations Research, 55(4), 2309-2335.
Andalib Ardakani, D., Soleimanizadeh, H., Mirfakhradini, S. H., & Soltanmohammadi, A. (2020). A fuzzy multi-objective optimization model for designing a sustainable supply chain forward network: A case study. Journal of Industrial and Systems Engineering, 13(1), 181-215.
Azadegan, A., Srinivasan, R., Blome, C., & Tajeddini, K. (2019). Learning from near-miss events:  An organizational learning perspective on supply chain disruption response. International Journal of Production Economics, 216(1), 215-226.
Azadegan, A., Syed, T. A., Blome, C., & Tajeddini, K. (2020). Supply chain involvement in business continuity management: effects on reputational and operational damage containment from supply chain disruptions. Supply Chain Management: An International Journal, 25(6), 747-772.
Biglar, A., Hamta, N., & Ahmadi Rad, M. (2022). Integration of liability payment and new funding entries in the optimal design of a supply chain network. Advances in Mathematical Finance and Applications, 7(3), 715-740.
Biglar, A., Hamta, N., & Ahmadi Rad, M. (2022). A Mathematical Programming Approach to Supply Chain Network Design considering Shareholder Value Creation. Discrete Dynamics in Nature and Society, 2022(Special Issue), 21-43.
Bilgen, B. (2010). Application of fuzzy mathematical programming approach to the production allocation and distribution supply chain network problem. Expert Systems with Applications, 37(6), 4488-4495.
Budak, A. (2020). Sustainable reverse logistics optimization with triple bottom line approach: An integration of disassembly line balancing. Journal of Cleaner Production, 270(1), 122475. 19.
Koc, C. (2017). An evolutionary algorithm for supply chain network design with assembly line balancing. Neural Computing and Applications, 28(11), 3183-3195. 
Ehsanifar, M., Ehtesham Rasi, R. (2017). An approach to improve customer satisfaction in logistics: the case of HEPCO. Journal of Industrial Strategic Management, 2(2), 49-66.
Elgazzar, S. H., Tipi, N. S., Hubbard, N. J., & Leach, D. Z. (2012). Linking supply chain processes’ performance to a company’s financial strategic objectives. European Journal of Operational Research, 223(1), 276-289.
Esmaeeli, H., Aleahmad, M. (2021). High Level Petri Nets Application for Reliability Visualization on Multi Echelon Supply Chain. In: Molamohamadi, Z., Babaee Tirkolaee, E., Mirzazadeh, A., Weber, GW. (eds) Logistics and Supply Chain Management. LSCM 2020. Communications in Computer and Information Science, 1458(1), 43-52.
Emamian, Y., Nakhai, I., & Eydi, A. (2018). Simultaneous reduction of emissions (CO2 and CO) and optimization of production routing problem in a closed-loop supply chain. Journal of Industrial and Systems Engineering, 11(2), 114-133.
Ghaithan, A. M., Attia, A., & Duffuaa, S. O. (2017). Multi-objective optimization model for a downstream oil and gas supply chain. Applied Mathematical Modelling, 52(1), 689-708.
Guo, Y., Hu, F., Allaoui, H., & Boulaksil, Y. (2019). A distributed approximation approach for solving the sustainable supply chain network design problem. International Journal of Production Research, 57(11), 3695-3718.
Hamta, N., Akbarpour Shirazi, M., Fatemi Ghomi, S. M. T., & Behdad, S. (2015). Supply chain network optimization considering assembly line balancing and demand uncertainty. International Journal of Production Research, 53(10), 2970-2994.
Hamta, N., Ehsanifar, M., Babai, A., & Biglar, A. (2021). Improving the Identification and prioritization of the most important risks of safety equipment in FMEA with a hybrid multiple criteria decision-making technique. Journal of applied research on industrial engineering, 8(Special Issue), 1-16.
Heydari, H., Paydar, M., Mahdavi, I., Khatayi, A. (2018). An integrated decision making model for manufacturing cell formation and supplier selection. Iranian Journal of Management Studies, 11(1), 113-145. https://doi.org/10.22059/ijms.2018.230426.672603.
Kadziński, M., Tervonen, T., Tomczyk, M. K., & Dekker, R. (2017). Evaluation of multi-objective optimization approaches for solving green supply chain design problems. Omega, 68(1), 168-184.
Karimi, R., Ghezavati, V. R., & Damghani, K. K. (2015). Optimization of multi-product, multi-period closed loop supply chain under uncertainty in product return rate: Case study in Kalleh dairy company. Journal of Industrial and Systems Engineering, 8(3), 95-114.
Kisomi, M. S., Solimanpur, M., & Doniavi, A. (2016). An integrated supply chain configuration model and procurement management under uncertainty: A set-based robust optimization methodology. Applied Mathematical Modelling, 40(17-18), 7928-7947.
Liu, S., & Papageorgiou, L. G. (2018). Fair profit distribution in multi-echelon supply chains via transfer prices. Omega, 80(1), 77-94.
Mogale, D. G., Ghadge, A., Kumar, S. K., & Tiwari, M. K. (2020). Modelling supply chain network for procurement of food grains in India. International Journal of Production Research, 58(21), 6493-6512.
Moradi, E., Ayough, A., Zandieh, M. (2019). Integrated process planning and active scheduling in a supply chain – A learnable architecture approach. Iranian Journal of Management Studies, 12(2), 307-333. https://doi.org/10.22059/ijms.2019.255363.673086.
Mota, B., Gomes, M. I., Carvalho, A., & Barbosa-Povoa, A. P. (2018). Sustainable supply chains: An integrated modeling approach under uncertainty. Omega, 77(1), 32-57.
Nagurney, A. (2010). Optimal supply chain network design and redesign at minimal total cost and with demand satisfaction. International Journal of Production Economics, 128(1), 200-208.
Nurjanni, K. P., Carvalho, M. S., & Costa, L. (2017). Green supply chain design: A mathematical modeling approach based on a multi-objective optimization model. International Journal of Production Economics, 183(1), 421-432.
Özceylan, E., Demirel, N., Çetinkaya, C., & Demirel, E. (2017). A closed-loop supply chain network design for automotive industry in Turkey. Computers & Industrial Engineering, 113(2), 727-745.
Özceylan, E., & Paksoy, T. (2013). Reverse supply chain optimisation with disassembly line balancing. International Journal of Production Research, 51(20), 5985-6001.
Paksoy, T., Özceylan, E., & Gökçen, H. (2012). Supply chain optimisation with assembly line balancing. International Journal of Production Research, 50(11), 3115-3136.
Ramezani, M., Kimiagari, A. M., Karimi, B., & Hejazi, T. H. (2014). Closed-loop supply chain network design under a fuzzy environment. Knowledge-Based Systems, 59(15-16), 108-120.
Ramezanian, R., & Khalesi, S. (2021). Integration of multi-product supply chain network design and assembly line balancing. Operational Research, 21(1), 453-483.
Rezaei, E., Paydar, M. M., & Safaei, A. S. (2020). Customer relationship management and new product development in designing a robust supply chain. RAIRO-Operations Research, 54(2), 369-391.
Sadeghi Moghadam, M., Momeni, M., Nalchigar, S. (2009). Material flow modeling in supply chain management with genetic algorithm approach. Industrial Management Journal, 1(2), 71-88.
Sawik, T. (2009). Coordinated supply chain scheduling. International Journal of Production Economics, 120(2), 437-451.
Schulze, M., Seuring, S., & Ewering, C. (2012). Applying activity-based costing in a supply chain environment. International Journal of Production Economics, 135(2), 716-725.
Taheri, S., & Beheshtinia, M. (2019). A genetic algorithm developed for a supply chain scheduling problem. Iranian Journal of Management Studies, 12(2), 281-306. https://doi.org/10.22059/ijms.2019.254633.673069.
Tirkolaee, E. B., Mardani, A., Dashtian, Z., Soltani, M., & Weber, G. W. (2020). A novel hybrid method using fuzzy decision making and multi-objective programming for sustainable-reliable supplier selection in two-echelon supply chain design. Journal of Cleaner Production, 250, 119517.
Validi, S., Bhattacharya, A., & Byrne, P. J. (2015). A solution method for a two-layer sustainable supply chain distribution model. Computers & Operations Research, 54, 204-217.
Varsei, M., Soosay, C., Fahimnia, B., & Sarkis, J. (2014). Framing sustainability performance of supply chains with multidimensional indicators. Supply Chain Management: An International Journal, 19(3), 242-257.
Yeung, W. K., Choi, T. M., & Cheng, T. C. E. (2011). Supply chain scheduling and coordination with dual delivery modes and inventory storage cost. International Journal of Production Economics, 132(2), 223-229.
Yi, P., Huang, M., Guo, L., & Shi, T. (2016). A retailer oriented closed-loop supply chain network design for end of life construction machinery remanufacturing. Journal of Cleaner Production, 124, 191-203.
Yolmeh, A., & Saif, U. (2021). Closed-loop supply chain network design integrated with assembly and disassembly line balancing under uncertainty: An enhanced decomposition approach. International Journal of Production Research, 59(9), 2690-2707.
Interdisciplinary Journal of Management Studies (Formerly known as Iranian Journal of Management Studies)
Volume 16, Issue 1
January 2023
Pages 61-77

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