A simulation study for a hybrid inventory control strategy with advance demand information

Choosing the appropriate production and inventory control strategy is a key factor for the success of modern enterprises. Some industries adopt a Make-To-Order (MTO) policy to improve their punctuality and flexibility, while others adopt a Make-To-Stock (MTS) policy to minimise and control the inventory. This study proposes a hybrid strategy combining MTS and MTO with prioritisation. In the proposed strategy, the pull policy is considered for regular demands while a push policy with priority is applied to customers who notify their demand needs in advance. Through a set of simulation experiments this strategy is proved to be of great effectiveness.

[1]  G. Reiner,et al.  Customized supply chain design: Problems and alternatives for a production company in the food industry. A simulation based analysis , 2004 .

[2]  Yannick Frein,et al.  Comparison among three pull control policies: kanban, base stock, and generalized kanban , 2000, Ann. Oper. Res..

[3]  Mary K. Vernon,et al.  Re-Examining the Performance of MRP and Kanban Material Control Strategies for Multi-Product Flexible Manufacturing Systems , 2004 .

[4]  Diwakar Gupta,et al.  Make-to-order, make-to-stock, or delay product differentiation? A common framework for modeling and analysis , 2004 .

[5]  D. P. Donk,et al.  Combined make-to-order and make-to-stock in a food production system , 2004 .

[6]  Asbjoern M. Bonvik,et al.  A comparison of production-line control mechanisms , 1997 .

[7]  Paul H. Zipkin,et al.  Foundations of Inventory Management , 2000 .

[8]  Yves Dallery,et al.  Integrating advance order information in make-to-stock production systems , 2002 .

[9]  John A. Buzacott,et al.  Stochastic models of manufacturing systems , 1993 .

[10]  Ananth Krishnamurthy,et al.  Performance analysis of single stage kanban controlled production systems using parametric decomposition , 2006, Queueing Syst. Theory Appl..

[11]  Joseph Geunes,et al.  Impact of introducing make-to-order options in a make-to-stock environment , 2006, Eur. J. Oper. Res..

[12]  Benita M. Beamon,et al.  A hybrid push/pull control algorithm for multi-stage, multi-line production systems , 2000 .

[13]  Yves Dallery,et al.  Efficient Scheduling Rules in a Combined Make-to-Stock and Make-to-Order Manufacturing System , 2004, Ann. Oper. Res..

[14]  Heinrich Kuhn,et al.  Analysis of production control systems kanban and CONWIP , 1996 .

[15]  Ananth Krishnamurthy,et al.  Kanban-based pull systems with advance demand information , 2009 .

[16]  S.-T. Yee.  Impact analysis of customized demand information sharing on supply chain performance , 2005 .

[17]  Jeffrey K. Liker,et al.  A simulation study of pull system responsiveness considering production condition influences , 2007 .

[18]  George Liberopoulos,et al.  Tradeoffs between base stock levels, numbers of kanbans, and planned supply lead times in production/inventory systems with advance demand information , 2005 .

[19]  Yves Dallery,et al.  An Analytical Method for Performance Evaluation of Kanban Controlled Production Systems , 1996, Oper. Res..

[20]  George Liberopoulos,et al.  Unified Modelling Framework of Multi-Stage Production-Inventory Control Policies with Lot Sizing and Advance Demand Information , 2003 .

[21]  Cathal Heavey,et al.  A review and comparison of hybrid and pull-type production control strategies , 2005 .

[22]  Ananth Krishnamurthy,et al.  Pull systems with advance demand information , 2005, Proceedings of the Winter Simulation Conference, 2005..

[23]  Chetan Soman,et al.  Capacitated planning and scheduling for combined make-to-order and make-to-stock production in the food industry: An illustrative case study , 2007 .

[24]  Ying Zhang,et al.  A hybrid inventory control system approach applied to the food industry , 2007, 2007 Winter Simulation Conference.

[25]  Özalp Özer,et al.  Inventory Control with Limited Capacity and Advance Demand Information , 2004, Oper. Res..