Abstract
The objective of this research approach is to improve the responsiveness and agility of the supply chain network by considering the allocation of inventory control, especially for the allocation of safety stock. This is achieved through considering the effect of components interdependencies and offering guaranteed lead times. An analytical model is presented in this paper, which is supported by discrete event simulation model in order to investigate the effect of material interdependency on the reduction to safety stock allocation. A case example from lead acid battery manufacturing supply chain network is used to demonstrate the applicability of the models. The results, by applying design structure matrix (DSM), showed that less material interdependency reduces the safety stock allocation significantly. The material interdependencies are reduced through clustering operation. The results also showed that reduction of material interdependency reduces the unnecessary investment in inventory management. The difference between the presented analytical model and the discrete event simulation is not significant, which also validate the proposed modeling approach.
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References
Box G., Jenkins G, Reinsel G (1994) Time series analysis: forecasting and control, 3rd Edition. Holden-Day San Francisco
Bucklin, L.P.: Postponement, speculation and the structure of distribution channels. Journal of Marketing Research (JMR) 2(1), 26–31 (1965)
Collier D (1980) Justifying component part standardization. In: Proceedings fo the 12th National AIDS Meeting, American Institute for Decision Sciences, Las Vegas, NV, p 405
Collier, D.: The measurement and operating benefits of component part commonality. Decision Sciences 12(1), 85–96 (1981)
Evans, D.: A note on modular design - a special case in nonlinear programming. Operations Research 18(3), 562–564 (1970)
Evans, D.H.: Modular design - A special case in nonlinear programming. Operations Research 11(4), 637–647 (1963)
Graves, S.C.: A single-item inventory model for a nonstationary demand process. Manufacturing & Service Operations Management 1(1), 50 (1999)
Graves, S.C., Willems, S.P.: Strategic inventory placement in supply chains: Nonstationary demand. Manufacturing & Service Operations Management 10(2), 278–287 (2008)
Graves, S.C., Willems, S.P., Zipkin, P.: Optimizing strategic safety stock placement in supply chains. Manufacturing & Service Operations Management 2(1), 68 (2000)
Jiao, J., Tseng, M.M.: Understanding product family for mass customization by developing commonality indices. Journal of Engineering Design 11(3), 225–243 (2000)
Kristianto, Y., Helo, P.: Strategic thinking in supply and innovation in dual sourcing procurement. International Journal of Applied Management Science 1(4), 401–419 (2009)
Kristianto, Y., Helo, P.: Built-to-order supply chain: response analysis with control model. International Journal of Procurement Management 3(2), 181–198 (2010)
Lee, H.L.: Effective inventory and service management through product and process redesign. Operations Research 44(1), 151 (1996)
Lee, H.L., Padmanabhan, V.: Information distortion in a supply chain: The bullwhip effect. Management Science 43(4), 546 (1997)
Levén E, Segerstedt A (2004) Inventory control with a modified croston procedure and erlang distribution. International Journal of Production Economics 90(3):361 – 367, production Control and Scheduling
Martin M, Ishii K (1996) Design for variety: a methodology for understanding the costs of product proliferation. In: Wood K (ed) Design Theory and Methodology - DTM’96, ASME, Irivine, CA, 96-DETC/DTM-1610
Mikkola, J.H.: Management of product architecture modularity for mass customization: Modeling and theoretical considerations. IEEE Transactions on Engineering Management 54(1), 57–69 (2007)
Neale, J.J., Willems, S.P.: Managing inventory in supply chains with nonstationary demand. Interfaces 39(5), 388–399 (2009)
Pagh, J.D., Cooper, M.C.: Supply chain postponement and speculation strategies: How to choose the right strategy. Journal of Business Logistics 19(2), 13–33 (1998)
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Nugroho, Y.K., Shamsuzzoha, A., Helo, P.T. (2011). Effect of component interdependency on inventory allocation. In: Reiner, G. (eds) Rapid Modelling and Quick Response. Springer, London. https://doi.org/10.1007/978-1-84996-525-5_18
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DOI: https://doi.org/10.1007/978-1-84996-525-5_18
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