The material substitution problem is a critical decision issue in the assembly industry. In practice, this problem is usually solved with managers’ experiences. However, the management objectives of material substitution are various and sometimes there are conflicts between different departments. Therefore, it needs a comprehensive analysis to assess the effectiveness of adopting substitution material under different management objectives. This research uses simulation model to analyze the effectiveness of material substitution policy which includes external substitution, internal substitution and general use of material. Full factorial experimental design was applied to find the performance of proposed material substitution policy, and order quantity, purchase lead-time, due-date variance, order arrival interval, and delay cost were chosen as independent variables. The average flow time, order delay time, order fulfillment rate, and system cost were chosen as dependent variables. Experimental results showed that material substitution policies are significant on all dependent variables. Especially the external substitution policy performed better than the others in the observed four performance indices. Through external substitution policy can improve order fulfillment rate and reduce average flow time. That is, applying external substitution policy can make a great improvement in customer satisfaction which is the most impact factor in satisfying customers under the mass customization environment.
Aydin, A.O., and Güngör, A. (2005). Effective relational database approach to represent bills-of-materials. International Journal of Production Research, 43(6), 1143-1170.
Balakrishnan, A., and Geunes, J. (2000). Requirements Planning with Substitutions: Exploiting Bill-of-Materials Flexibility in Production Planning. Manufacturing & Service Operations Management, 2(2), 166-185.
Boynton, A.C., Victor, B., and Pine II, B.J. (1993). New Competitive Strategies: Challenges to Organizations and Information Technology. IBM Systems Journal, 132(1), 40-64.
Duray, R., Ward, P.T., Milligan, G.W., and Berry, W.L. (2000). Approaches to mass customization: configurations and empirical validation. Journal of Operations Management, 18(6), 605-625.
Eastwood, M.A. (1996). Implementing Mass Customization. Computers in Industry, 30(3), 171-174.
Frutos, J.D., and Borenstein, D. (2004). A framework to support customer–company interaction in mass customization environments. Computers in Industry, 54(2), 115-135.
Joneja, A., and Lee, N.K.S. (1998). Automated configuration of parametric feeding tools for mass customization. Computers and Industrial Engineering, 35(3-4), 463-469.
Kusiak, A., and Huang, C.C. (1996). Development of modular products. IEEE Transactions on components, 19(4), 523-538.
Lyon, P.R., Milne, J., Orzell, R., and Rice, R. (2001). Matching Assets with Demand in Supply-Chain Management at IBM Microelectronics. Interfaces, 31(1), 108-124.
Mohebbi, E., and Choobineh, F. (2005). The impact of component commonality in an assemble-to-order environment under supply and demand uncertainty. Omega, 33(6), 472-482.
Olsen, K.A., Satre, P., and Thorstenson, A. (1997). A procedure-oriented generic bill of materials. Computers and Industrial Engineering, 32(1), 29-45.
Orlicky, J.A. (1974). Material Requirements Planning: The New Way of Life in Production and Inventory Management. McGraw-Hill, Inc.
Partanen, J., and Haapasalo, H. (2004). Fast production for order fulfillment: Implementing mass customization in electronics industry. International Journal of Production Economics, 90(2), 213-222.
Ram, B., M. Reza Naghshineh-Pour, and Yu, X. (2006). Material requirements planning with flexible bills-of-material. International Journal of Production Research, 44(2), 399-415.
Selladurai, R.S. (2004). Mass Customization in Operations Management: Oxymoron or Reality?. Omega, 32(4), 295-300.
Silveira, G.,D., Borenstein, D., and FlaHvio, S.F. (2001). Mass customization: Literature review and research directions. International Journal of Production Economics, 72(1), 1-13.
Teunter, R., and Laan, E. (2002). On the Non-Optimality of the Average Cost Approach for Inventory Models with Remanufacturing. International Journal of Production Economics, 79(1), 67-73.
Tu, Q., Vonderembse, M.A., and Ragu-Nathan, T.S. (2001). The impact of time-based manufacturing practices on mass customization and value to customer. Journal of Operations Management, 19(2), 201-217.
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