Evaluating and Selecting Recycling Centers in Lead-Acid Battery Supply Chain using DEA: A Case Study
الموضوعات :Mona Ghalandari 1 , Mohammad Amirkhan 2 , hossein Amoozad-khalili 3
1 - Department of Industrial Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran
2 - Department of Industrial Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran.
3 - Department of Industrial Engineering, Sari Branch, Islamic
Azad University, Sari, Iran
الکلمات المفتاحية: Supply Chain, DEA, Efficiency, Sustainability, Lead-Acid Battery,
ملخص المقالة :
Reducing the manufacturing costs of the products is considered of the main factors for lead-acid battery (LAB) manufacturers 'sustainability and survival in the automotive industry. Then in order to meaningfully decrease the due costs and enhance the competitive potential of the manufacturers in this field, it’s important to choose the suitable sites for recycling centers in this industry's supply chain. In the present study, data envelopment analysis (DEA) has been utilized for evaluating and choosing the recycling centers as befitting for the supply chain of LABs in the automotive industry. Pursuant to DEA and a set of criteria, as being critical for decision makers in this filed, various locations are evaluated. As this method prescribes, the locations are ranked using the maximum scores of efficiencies and after that, more appropriate centers are picked and the inappropriate ones get removed. A LAB supply chain related case study in the automotive industry has been employed for evaluating the influencing power and efficiency of proposed method and following that, a number of beneficial management results have been extracted.
[1] P. Kurzweil, "Gaston Planté and his invention of the lead–acid battery—The genesis of the first practical rechargeable battery", Journal of Power Sources, Vol. 195, No. 14: 4424-4434, 2010.
[2] D. Pavlov, Lead-acid batteries: science and technology. 2nd edition, 2017, Elsevier.
[3] A. Charnes, W.W. Cooper, and E. Rhodes, "Measuring the efficiency of decision making units", European journal of operational research, Vol. 2, No. 6: 429-444, 1978.
[4] R.D. Banker, A. Charnes, and W.W. Cooper, "Some models for estimating technical and scale inefficiencies in data envelopment analysis", Management science, Vol. 30, No. 9: 1078-1092, 1984.
[5] W.-f. Shen, D.-q. Zhang, W.-b. Liu, and G.-l. Yang, "Increasing discrimination of DEA evaluation by utilizing distances to anti-efficient frontiers", Computers & Operations Research, Vol. 75, 163-173, 2016.
[6] M. Ghadami, H. Sahebi, M. Pishvaee, and H. Gilani, "A sustainable cross-efficiency DEA model for international MSW-to-biofuel supply chain design", RAIRO-Operations Research, Vol. 55, S2653-S2675, 2021.
[7] S.-M. Hosseini-Motlagh, M.R.G. Samani, and S. Cheraghi, "Robust and stable flexible blood supply chain network design under motivational initiatives", Socio-Economic Planning Sciences, Vol. 70,100725, 2020.
[8] Z. Mohtashami, A. Bozorgi-Amiri, and R. Tavakkoli-Moghaddam, "A two-stage multi-objective second generation biodiesel supply chain design considering social sustainability: A case study", Energy, Vol. 233,121020, 2021.
[9] H. Alidrisi, "DEA-Based PROMETHEE II distribution-center productivity model: Evaluation and location strategies formulation", Applied Sciences, Vol. 11, No. 20: 9567, 2021.
[10] I. Rahimi, A. Emrouznejad, S.H. Tang, and A. Ahmadi, "Trade-off in facility location and facility efficiency in supply chain network: a data envelopment analysis approach", International Journal of Industrial and Systems Engineering, Vol. 36, No. 4: 471-495, 2020.
[11] G. Cattani, "Combining data envelopment analysis and Random Forest for selecting optimal locations of solar PV plants", Energy and AI, Vol. 11: 100222, 2023.
[12] M. Tavassoli and R. Farzipoor Saen, "Sustainability measurement of combined cycle power plants: a novel fuzzy network data envelopment analysis model", Annals of Operations Research, 2023.
