A distributed and collaborative model for product design selection considering its supply chain costs and environmental footprint

References

• Afrouzy, Z. A., Nasseri, S. H., & Mahdavi, I. (2016). A genetic algorithm for supply chain configuration with new product development. Computers & Industrial Engineering, 101(C), 440–454. https://doi.org/10.1016/j.cie.2016.09.008
   Google Scholar
• Agard, B. (2002). « Contribution à une méthodologie de conception de produits à forte diversité » [PhD thesis]. National Polytechnic Institute of Grenoble.
   Google Scholar
• Aguila, J. O., Elmaraghy, W., & Elmaraghy, H. (2019). Impact of risk attitudes on the concurrent design of supply chains and product architectures. Procedia CIRP, 81(2019), 974–979. https://doi.org/10.1016/j.procir.2019.03.237
   Google Scholar
• Avci, M. G., & Selim, H. (2016). A multi-agent system model for supply chains with lateral preventive transshipments: Application in a multi-national automotive supply chain. Computers in Industry, 82, 28–39. https://doi.org/10.1016/j.compind.2016.05.005
   Web of Science ®Google Scholar
• Ballouki, I., Douimi, M., & Ouzizi, L. (2017). Decision support tool for supply chain configuration considering new product re-design: An agent-based approach. Journal of Advanced Manufacturing Systems, 16(4), 291–315. https://doi.org/10.1142/S0219686717500184
   Web of Science ®Google Scholar
• Ballouki, I., Douimi, M., & Ouzizi, L. (2018). ‘Decision support tool selection for Eco-design integration into the simultaneous design of product and its supply chain’. Journal of Environmental Assessment Policy and Management, Volume 20(Issue 02).
   Google Scholar
• Chen, S. J., & Hwang, C. L. (1992). Fuzzy multiple attribute decision making: Methods and applications. Springer-Verlag.
   Google Scholar
• Chiu, M.-C., Chang, C.-H., Chen, Y.-T., Chiou, J.-Y., & Chang, Y.-J. (2016). Redesign for sustainability and assemblability using particle swarm optimization method. Journal of Industrial and Production Engineering, 33(2), 103–113. https://doi.org/10.1080/21681015.2015.1111264
   Web of Science ®Google Scholar
• Chiu, M. C., & Okudan, G. (2014). An investigation on the impact of product modularity level on supply chain performance metrics: An industrial case study. Journal of Intelligent Manufacturing, 25(1), 129–145. https://doi.org/10.1007/s10845-012-0680-3
   Web of Science ®Google Scholar
• Chouinard, M. (2007). Modélisation et conception de boucles d’approvisionnement: Contexte multi-produit, multi-état et multi-alternative de traitement [Doctoral thesis]. Laval University.
   Google Scholar
• Chung, W.-H., Kremer, G., & Wysk, R. (2014). A modular design approach to improve product life cycle performance based on the optimization of a closed-loop supply chain. Journal of Mechanical Design, 136(2), 021001. Paper No: MD-12-1278. https://doi.org/10.1115/1.4025022
   Web of Science ®Google Scholar
• Deloach, S. A., Wood, M. F., & Sparkman, C. H. (2001). Multiagent Systems engineering. International Journal of Software Engineering and Knowledge Engineering, 11(n 3), 231–258. https://doi.org/10.1142/S0218194001000542
   Web of Science ®Google Scholar
• Dufrene, M. (2015). Proposition d’un cadre méthodologique comme support aux approaches d’écoconception en entreprise: Exigences et conceptualisation pour une plateforme logicielle [Phd dissertation]. Université Grenoble ALPES.
   Google Scholar
• El Hadj Khalef, R., Agard, B., & Penz, B. (2011). Simultaneous design of a product family and its related supply chain using a Tabu search algorithm. International Journal of Production Research, 49(19), 5637–5656. https://doi.org/10.1080/00207543.2010.519737
   Web of Science ®Google Scholar
• ElMaraghy, H. A., & Mahmoudi, N. (2009). Concurrent design of product modules structure and global supply chain configurations. International Journal of Computer Integrated Manufacturing, 22(6), 483–493. https://doi.org/10.1080/09511920802389553
   Web of Science ®Google Scholar
• Feng, T., & Zhang, F. (2013). The impact of modular assembly on supply chain efficiency. Production and Operations Management, Vol. 0(No. 0), 1–17.
   Google Scholar
• Fiksel, J. R. (2009). Design for environment: A guide to sustainable product development. Sustainable Development.
   Google Scholar
• Fixson, S. K. (2007). Modularity and commonality research: Past developments and future opportunities. Concurrent Engineering, 15(2), 85–111. https://doi.org/10.1177/1063293X07078935
   Web of Science ®Google Scholar
• Fung, R., Chen, Y., & Tang, J. (2007). A quality-engineering-based approach for conceptual product design. The International Journal of Advanced Manufacturing Technology, 32(11-12), 1064–1073. https://doi.org/10.1007/s00170-006-0434-5
   Web of Science ®Google Scholar
• Gokhan, N. M. (2007). Development of a simultaneous design for supply chain process for the optimization of the product design and supply chain configuration problem [Doctoral thesis]. Pittsburgh University.
   Google Scholar
• Gupta, S., & Krishnan, V. (1999). Integrated component and supplier selection for a product family. Journal Production and Operations Management, 8(2), 163–181. https://doi.org/10.1111/j.1937-5956.1999.tb00368.x
   Web of Science ®Google Scholar
• Hermenau, U., Hansen, S., & Abele, E. (2005). Integration of life cycle design in industrial practice: problems and solutions. The 4th International Symposium on Environmentally Conscious Design and Inverse Manufacturing.
   Google Scholar
• Hong, I., Su, J. C. P., Chu, C.-H., & Yen, C.-Y. (2018). Decentralized decision framework to coordinate product design and supply chain decisions: Evaluating tradeoffs between cost and carbon emission. Journal of Cleaner Production, 204, 107–116. https://doi.org/10.1016/j.jclepro.2018.08.239
   Web of Science ®Google Scholar
• Huang, G. Q., Zhang, X. Y., & Lo, V. H. Y. (2007). ‘Integrated configuration of platform products and supply chains for mass customization: A game-theoritic approach. IEEE Transactions on Engineering Management, 54(1), 156–171. https://doi.org/10.1109/TEM.2006.889074
   Web of Science ®Google Scholar
• ISO TR/14062. (2002). Environmental management-Integrating environmental aspects into product design and development: International Organization for Standardization.
   Google Scholar
• Krikke, H., Bloemhof-Ruwaard, J., & Van Wassenhove, L. N. (2003). Concurrent product and closed-loop supply chain design with an application to refrigerators. International Journal of Production Research, 41(16), 3689–3719. https://doi.org/10.1080/0020754031000120087
   Web of Science ®Google Scholar
• Labbi, O., Ouzizi, L., & Douimi, M. (2017). Simultaneous design of a product and its closed-loop supply chain: An optimization model. International Journal of Manufacturing (in press). https://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=ijrem
   PubMedGoogle Scholar
• Lamothe, J., Hadj-Hamou, K., & Aldanondo, M. (2006). An optimization model for selecting a product family and designing its supply chain. European Journal of Operational Research, 169(Issue 3), 1030–1047. https://doi.org/10.1016/j.ejor.2005.02.007
   Web of Science ®Google Scholar
• Lavigne, B., Agard, B., & Penz, B. (2012). Mutual impacts of product standardization and supply chain design. International Journal of Production economics. Advances in Optimization and Design of Supply Chains, 135(1), 50–60.
   Google Scholar
• Lavigne, B., Agard, B., & Penz, B. (2014). Environmental constraints in joint product and supply chain design optimization. Computers & Industrial Engineering, 76, 16–22. https://doi.org/10.1016/j.cie.2014.07.014
   Web of Science ®Google Scholar
• Lee, H. L., & Billington, C. (1992). Managing supply chain inventory: Pitfalls an opportunity. Sloan Management Review, 33(3), 65–73.
   Google Scholar
• Lee, H. L., & Sasser, M. M. (1995). Product universality and design for supply chain management. Journal of Production Planing & Control: The Management of Operations, 6(3), 270–277. https://doi.org/10.1080/09537289508930279
   Web of Science ®Google Scholar
• Liu, S., Lazaros, G., Papageorgiou, & Shah, N. (2020). Optimal design of low-cost supply chain networks on the benefits of new product formulation. Computers & Industrial Engineering, Volume 139. https://www.sciencedirect.com/science/article/abs/pii/S0360835219306588
   Web of Science ®Google Scholar
• Minsky, M. (1985). The society of mind. Simon & Schuster.
   Google Scholar
• Nepal, B., Monplaisir, L., & Famuyiwa, F. (2010). Supply chain configuration model for new product development: A multi-objective approach. POMS 21st Annual Conference, Vancouver, Canada May 7 to May 10 (pp. 7107–7134).
   Google Scholar
• Philip, N., Okudan, G. E., Haapala, K. R., & Kim, K. (2012). Computer-aided generation of modular designs considering component end-of-life options: Implications for the supply chain. ASME. International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Volume 5: 6th International Conference on Micro- and Nanosystems; 17th Design for Manufacturing and the Life Cycle Conference (pp. 529–539).
   Google Scholar
• Rehman, F., & Yan, X. T. (2003). Product design elements as means to realize functions in mechanical conceptual design. Proceedings of 14th International Conference on Engineering Design ICED 03, Stockholm, Sweden (pp. 213).
   Google Scholar
• Rong, Z., Yang, Z., Li, Y., Chen, K., & Dan, B. (2017). Modular product design based on the supply chain network. Advances in Mechanical Engineering, 9(10), 1–13. https://doi.org/10.1177/1687814017732308
   Web of Science ®Google Scholar
• Sheldon, D. F., Perks, R., Jackson, M., Miles, B. L., & Holland, J. (1990). ‘’Designing for whole life costs at the concept stage’’. Journal of Engineering Design, 1(2), 131–145. https://doi.org/10.1080/09544829008901649
   Web of Science ®Google Scholar
• Shidpour, H., Bernardb, A., & Shahrokhic, M. (2013). A group decision-making method based on intuitionistic fuzzy set in the three dimensional concurrent engineering environment: A multiobjective programming approach. Forty Sixth CIRP Conferences on Manufacturing Systems 2013. Procedia CIRP 7 (pp. 533–538).
   Google Scholar
• Su, J. C. P., Chu, C.-H., & Wang, Y.-T. (2012). A decision support system to estimate the carbon emission and cost of product designs. International Journal of Precision Engineering and Manufacturing, 13(7), 1037–1045. https://doi.org/10.1007/s12541-012-0135-y
   Web of Science ®Google Scholar
• Takami, M. A., Sheikh, R., & Sana, S. S. (2015). Product portfolio optimization using teaching-learning-based optimization algorithm: A new approach in supply chain management. International Journal of Systems Science: Operations & Logistics, https://doi.org/10.1080/23302674.2015.1090642.
   Google Scholar
• Ülkü, S., & Schmidt, G. M. (2011). Matching product architecture and supply chain configuration. Journal of Production and Operations Management, 20(1), 16–31. https://doi.org/10.1111/j.1937-5956.2010.01136.x
   Web of Science ®Google Scholar
• Waiss, H. S. C. (2017). Intégration des contraintes de désassemblage dans la conception modulaire de produits manufacturés”. Sustainable development context. Materials. Grenoble Alpes University.
   Google Scholar
• Xiao, A., Seepersad, C. C., Allen, J. K., Rosen, D. W., & Mistree, F. (2007). Design for manufacturing: Application of collaborative multidisciplinary decision-making methodology. Engineering Optimization, 39(4), 429–451. https://doi.org/10.1080/03052150701213104
   Web of Science ®Google Scholar
• Yang, D., Jiao, J., Ji, J., Du, J., Helo, P., & Valente, I. (2015). Joint optimization for coordinated configuration of product families and supply chains by a leader-follower Stackelberg game. European Journal of Operational Research, 246(1), 263–280. https://doi.org/10.1016/j.ejor.2015.04.022
   Web of Science ®Google Scholar
• Zhang, X., Huang, G. Q., & Rungtusanatham, M. J. (2008). Simultaneous configuration of platform products and manufacturing supply chains. International Journal of Production Research, 46(21), 6137–6162. https://doi.org/10.1080/00207540701324150
   Web of Science ®Google Scholar