Sustainable supply chain network design using lean principles

Document Type : Research/ Original/ Regular Article

Authors

Assistant Professor at Faculty of Industrial Engineering, Amir Kabir University of Technology.

Abstract

The design of sustainable supply chain networks has attracted more attention in recent years as it encompasses all three economic, social and environmental factors at the same time. The lean philosophy is to achieve a system that is free from any waste. There are different techniques to implement lean in the organization. Each of these techniques, through their effects, helps the organization to improve sustainability performances of the overall business. This paper proposed a multi objective mixed integer nonlinear programing for sustainable supply chain network design using lean techniques. The proposed model is aimed at maximizing social benefits while minimizing economic costs and environmental impacts. In this paper, 10 lean techniques with the effects of each are introduced, which calculate the impact of each of these techniques on different aspects of sustainability. we introduce a solution procedure based on linearization . Finally, a single aggregated objective function is derived using a fuzzy goal programming approach. In addition, sensitivity analysis is conducted to provide deeper understanding of the proposed model. The results show that lean implementation in supply chain design reduces costs, helps the organization to improve sustainability performances, and gives better results when compared to the non-compliant state.

Keywords


[1] Hombach, L.E., C. Büsing, and G. Walther, Robust and sustainable supply chains under market uncertainties and different risk attitudes – A case study of the German biodiesel market. European Journal of Operational Research, 2018. 269(1): p. 302-312.
[2] Ugarte, G.M., J.S. Golden, and K.J. Dooley, Lean versus green: The impact of lean logistics on greenhouse gas emissions in consumer goods supply chains. Journal of Purchasing and Supply Management, 2016. 22(2): p. 98-109.
[3] Afonso, H. and M.d.R. Cabrita, Developing a Lean Supply Chain Performance Framework in a SME: A Perspective Based on the Balanced Scorecard. Procedia Engineering, 2015. 131: p. 270-279.
[4] Das, K., Integrating lean systems in the design of a sustainable supply chain model. International Journal of Production Economics, 2018. 198: p. 177-190.
[5] Winkler, H., Closed-loop production systems—A sustainable supply chain approach. CIRP Journal of Manufacturing Science and Technology, 2011. 4(3): p. 243-246.
[6] Costantino, N., M. Dotoli, M. Falagario, and F. Sciancalepore, Fuzzy network design of sustainable supply chains. IFAC Proceedings Volumes, 2012. 45(6): p. 1284-1289.
[7] Ren, J., A. Manzardo, S. Toniolo, and A. Scipioni, Sustainability of hydrogen supply chain. Part II: Prioritizing and classifying the sustainability of hydrogen supply chains based on the combination of extension theory and AHP. International Journal of Hydrogen Energy, 2013. 38(32): p. 13845-13855.
[8] Govindan, K., A. Jafarian, R. Khodaverdi, and K. Devika, Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food. International Journal of Production Economics, 2014. 152: p. 9-28.
[9] Gonela, V., J. Zhang, A. Osmani, and R. Onyeaghala, Stochastic optimization of sustainable hybrid generation bioethanol supply chains. Transportation Research Part E: Logistics and Transportation Review, 2015. 77: p. 1-28.
[10] M.P, S., S. P.R, R. A, and B. P, Lean manufacturing practices in Indian manufacturing SMEs and their effect on sustainability performance. Journal of Manufacturing Technology Management, 2017. 28: p. 00-00.
[11] Bazaraa, M.S., H.D. Sherali, and C.M. Shetty, Nonlinear Programming: Theory and Algorithms. 2013: Wiley.
[12] Norouzi, N., R. Tavakkoli-Moghaddam, M. Ghazanfari, M. Alinaghian, and A. Salamatbakhsh, A New Multi-objective Competitive Open Vehicle Routing Problem Solved by Particle Swarm Optimization. Networks and Spatial Economics, 2011. 12.
[13] Glover, F. and E. Woolsey, Converting the 0-1 Polynomial Programming Problem to a 0-1 Linear Program. Operations Research, 1974. 22(1): p. 180-182.
[14] McCormick, G.P., Computability of global solutions to factorable nonconvex programs: Part I — Convex underestimating problems. Mathematical Programming, 1976. 10(1): p. 147-175.
[15] Bessis, J., Risk Management in Banking. 2011: Wiley.
[16] Torabi, S.A. and E. Hassini, An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets and Systems, 2008. 159(2): p. 193-214.
[17] Zimmermann, H.J., Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems, 1978. 1(1): p. 45-55.
[18] Li, X.-q., B. Zhang, and H. Li, Computing efficient solutions to fuzzy multiple objective linear programming problems. Fuzzy Sets and Systems, 2006. 157(10): p. 1328-1332.
[19] Werners, B.M. Aggregation Models in Mathematical Programming. 1988. Berlin, Heidelberg: Springer Berlin Heidelberg.
[20] Selim, H. and I. Ozkarahan, A supply chain distribution network design model: An interactive fuzzy goal programming-based solution approach. The International Journal of Advanced Manufacturing Technology, 2008. 36(3): p. 401-418.