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Supply chain focus dependent safety stock placement

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International Journal of Flexible Manufacturing Systems Aims and scope Submit manuscript

Abstract

Increasing globalization, growing product range diversity, and rising consumer awareness are making markets highly competitive, forcing supply chains to adapt constantly to different stimuli. Growing competition between supply chains (as well as players within them) is also warranting a priority for overall supply chain performance over the goals of individual players. It is now well established in the literature that, among the many order winners, both overall supply chain cost and responsiveness (i.e., supply chain lead time) are the most significant determinants of supply chain competitiveness. The literature, however, mostly focuses on supply chain cost minimization with rather simplistic treatment of responsiveness. By introducing the concept of a coefficient of inverse responsiveness (CIR), we facilitate efficient introduction of responsiveness related costs into the scheme of supply chain (SC) performance evaluation and/or optimization. Thus, our model aids supply chain managers in achieving better strategic fit between individual business unit strategies and overall supply chain requirements in terms of cost efficiency and responsiveness. In particular, it aids in strategic placement of safety stocks at different stages in the supply chain. Our model also offers managerial insights that help improve our intuitions into supply chain dynamics. The model is more suited for strategic SC alignment, for example, when dealing with product changeovers or introduction of new product, rather than for operational control.

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References

  • Axsäter S (1993) Continuous review policies for multi-level inventory systems with stochastic demand. In: Graves S, Rinnooy Kan A, Zipkin P (eds) Logistics of production and inventory. Elsevier Science, North Holland

  • Axsäter S, Rosling K (1993) Notes: installation vs. Echelon stock policies for multilevel inventory control. Manage Sci 39(10):1274–1280

    MATH  Google Scholar 

  • Ben-Daya M, Raouf A (1994) Inventory models involving lead time as decision variables. J Oper Res Soc 45:579–582

    Article  MATH  Google Scholar 

  • Bookbinder JH, Cakanyildirim M (1999) Random lead times and expedited orders in (Q, r) inventory systems. Eur J Oper Res 115:300–313

    Article  MATH  Google Scholar 

  • Cherukuri SS, Nieman RG, Sirianni NC (1995) Cycle time and the bottom line. Indust Eng 27(3):20–23

    Google Scholar 

  • Choi JW (1994) Investment in the reduction of uncertainties in just in time purchasing systems. Naval Res Logistics 41:257–272

    Article  MATH  Google Scholar 

  • Chopra S, Meindl P (2004) Supply chain management: strategy, planning and operation, 2nd edn. Pearson Education Inc., Upper Saddle River

    Google Scholar 

  • Chopra S, Reinhardt G, Dada M (2004) The effect of lead time uncertainty on safety stocks. Decis Sci 35(1):1–24

    Article  Google Scholar 

  • Clark A, Scarf H (1960) Optimal policies for a multi echelon inventory problem. Manage Sci 6:474–490

    Google Scholar 

  • Davis D, Buckler J, Mussomeli A, Kinzler D (2005) Inventory transformation: Revlon style. Supply Chain Manage Rev 9(5):53–59

    Google Scholar 

  • Eppen GD, Martin RK (1988) Determining safety stock in the presence of stochastic lead time and demand. Manage Sci 34(11):1380–1390

    MathSciNet  MATH  Google Scholar 

  • Ettl M, Feigin GE, Lin GY, Yao DD (2000) A supply network model with base—stock control and service requirements. Oper Res 48:216–232

    Article  Google Scholar 

  • Felgate R, Bott S, Harris C (2007) Get your timing right. Supply Manage 12(1):17

    Google Scholar 

  • Feller W (1960) An introduction to probability theory and its applications, vol I. Wiley, New York

    Google Scholar 

  • Fisher ML (1997) What is the right supply chain for your product? Harv Bus Rev 75(2):105–116

    Google Scholar 

  • Gallego G, Zipkin P (1999) Stock positioning and performance estimation in serial production-transportation systems. Manuf Serv Oper Manage 1(1):77–88

    Google Scholar 

  • Gaur V, Giloni A, Seshadri S (2005) Information sharing in a supply chain Under ARMA demand. Manage Sci 51(6):961–969

    Article  Google Scholar 

  • Glasserman P, Tayur S (1995) Sensitivity analysis for base stock levels in multi echelon production-inventory system. Manage Sci 41:216–232

    Google Scholar 

  • Glasserman P, Tayur S (1996) A simple approximation for a multi stage capacitated production inventory systems. Naval Res Logistics 43:41–58

    Article  MATH  Google Scholar 

  • Graves S (1985) Multi echelon inventory model for a repairable item with one for one replenishment. Manage Sci 31:1247–1256

    MathSciNet  MATH  Google Scholar 

  • Graves SC (1988) Safety stocks in manufacturing systems. J Manuf Oper Manage 1:67–101

    MathSciNet  Google Scholar 

  • Graves SC, Willems SP (2003) Supply chain design: safety stock placement and supply chain configuration. In: de Kok AG, Graves SC (eds) Handbooks in operations research and management science, supply chain management: design, coordination and operation, Chap 3, vol 11. Elsevier BV, Amsterdam, The Netherlands

    Google Scholar 

  • Hanssmann F (1959) Optimal inventory location and control in production and distribution networks. Oper Res 7:483–498

    MathSciNet  Google Scholar 

  • Hill T (1993) Manufacturing strategy: text and cases, 2nd edn. IRWIN, Illinois

    Google Scholar 

  • Kapuscinski R, Tayur S (1999) Optimal policies and simulation based optimization for capacitated production inventory systems. In: Tayur S, Ganeshan R, Magazine MJ (eds) Quantitative models for supply chain management. Kluwer Academic Publishers, Boston

    Google Scholar 

  • Lee HL, Billington C (1993) Material management in decentralized supply chains. Oper Res 41(5):835–847

    MATH  Google Scholar 

  • Lee HL, Moinzadeh K (1987a) Two parameter approximations for multi echelon repairable inventory models with batch ordering policy. IIE Trans 19:140–149

    Article  Google Scholar 

  • Lee HL, Moinzadeh K (1987b) Operating characteristics of a two echelon inventory system for repairable and consumable items under batch ordering and shipment policy. Naval Res Logistics Quart 34:365–380

    Article  MATH  Google Scholar 

  • Lee Y, Zipkin P (1992) Tandem queues with planned inventories. Oper Res 40:936–947

    Article  MATH  Google Scholar 

  • Moon I, Choi S (1998) Technical note: a note on lead time and distributional assumptions in continuous review inventory models. Comput Oper Res 25(11):1007–1012

    Article  MathSciNet  MATH  Google Scholar 

  • Nazzal D, Mollaghasemi M, Anderson D (2006) A simulation-based evaluation of the cost of cycle time reduction in Agere systems wafer fabrication facility—a case study. Int J Prod Econ 100:300–313

    Article  Google Scholar 

  • Rosling K (1989) Optimal inventory policies for assembly systems under random demands. Oper Res 37:565–579

    MathSciNet  MATH  Google Scholar 

  • Ryu SW, Lee KK (2003) A stochastic inventory model of dual sourced supply chain with lead-time reduction. Int J Prod Econ 81–82:513–524

    Article  Google Scholar 

  • Simchi-Levi D, Zhao Y (2005) Safety stock positioning in supply chain with stochastic lead times. Manuf Serv Oper Manage 7(4):295–318

    Article  Google Scholar 

  • Simpson KF (1958) In process inventories. Oper Res 6:863–873

    MathSciNet  Google Scholar 

  • Sourirajan K, Ozsen L, Uzsoy R (2007) A single-product network design model with lead time and safety stock considerations. IIE Trans 39:411–424

    Article  Google Scholar 

  • Speck C, vander Wal J (1991) The capacitated multi echelon inventory system with serial structure: 1. The “push-ahead” effect. Memorandum COSOR 91-39, Eindhoven University of Technology, Eindhoven, The Netherlands

  • Upton DM (1997) Process range in manufacturing: an empirical study of flexibility. Manage Sci 43(8):1079–1092

    MATH  Google Scholar 

  • Van Houtum GJ, Inderfurth K, Zijm WHM (1996) Materials coordination in stochastic multi echelon systems. Eur J Oper Res 95:1–23

    Article  MATH  Google Scholar 

  • Vanteddu G, Chinnam RB, Yang, K (2006) A performance Comparison tool for Supply Chain management. Int J Logistics Syst Manage 2(4):342–356

    Google Scholar 

  • Yang B, Geunes J (2007) Inventory lead time planning with lead-time sensitive demand. IIE Trans 39(5):439

    Article  Google Scholar 

Download references

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Correspondence to Ratna Babu Chinnam.

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Vanteddu, G., Chinnam, R.B., Yang, K. et al. Supply chain focus dependent safety stock placement. Int J Flex Manuf Syst 19, 463–485 (2007). https://doi.org/10.1007/s10696-008-9050-z

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  • DOI: https://doi.org/10.1007/s10696-008-9050-z

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