Capacity Coordination under Demand Uncertainty in a Hybrid Make-To-Stock/Make-To-Order Environment: A System Dynamics Approach

Hybrid Make-To-Stock (MTS)/ Make-To-Order (MTO) production systems have recently attracted practitioners and academicians in the field of operations management, since these systems benefit from both stock-based and order-driven strategies. In this paper, capacity coordination dynamics of a hybrid MTS/MTO production system is addressed whose continuous production line comprises three workstations. Also, product portfolio of the considered system includes three kinds of products; pure MTS, pure MTO, and hybrid MTS/MTO. In the developed model, system performance is explored and assessed in terms of system delivery lead time. To do so, three capacity coordination rules are studies; simple average of expected demands, weighted average of expected demands, and the dynamic mechanism upon the difference between target and actual delivery lead times. Moreover, effects of demand uncertainty are taken into account

[1]  Brian G. Kingsman,et al.  Responding to customer enquiries in make-to-order companies Problems and solutions , 1996 .

[2]  Patroklos Georgiadis,et al.  “The efficiency of alternative control mechanisms in a MTO three-stage tandem production/inventory system” , 2008 .

[3]  A. Federgruen,et al.  The Impact of Adding a Make-To-Order Item to a Make-To-Stock Production System , 1999 .

[4]  Jayendran Venkateswaran,et al.  Closed-Loop Supply Chain Stability under Different Production-Inventory Policies , 2008 .

[5]  Roberto Poles,et al.  Inventory control in closed loop supply chain using system dynamics , 2009 .

[6]  David F. Pyke,et al.  Inventory management and production planning and scheduling , 1998 .

[7]  V. Donk.  Make to stock or make to order: the decoupling point in the food processing industries , 2001 .

[8]  H Tsubone,et al.  Production planning system for a combination of make-to-stock and make-to-order products , 2002 .

[9]  Zofia Verwater-Lukszo,et al.  System-dynamics modelling to improve complex inventory management in a batch-wise plant , 2005 .

[10]  T. Williams.  Special products and uncertainty in production/inventory systems☆ , 1984 .

[11]  A. Al-Refaie,et al.  A System Dynamics Approach to Reduce Total Inventory Cost in an Airline Fueling System , .

[12]  Masoud Rabbani,et al.  Novel bi-level hierarchical production planning in hybrid MTS/MTO production contexts , 2013 .

[13]  A. Marucheck,et al.  Strategic issues in make-to-order manufacturing , 1986 .

[14]  S. Hoekstra,et al.  Integral Logistic Structures: Developing Customer-Oriented Goods Flow , 1992 .

[15]  J. Forrester.  Industrial Dynamics , 1997 .

[16]  J Swanson,et al.  Business Dynamics—Systems Thinking and Modeling for a Complex World , 2002, J. Oper. Res. Soc..

[17]  Jan Olhager,et al.  Strategic positioning of the order penetration point , 2003 .

[18]  J. Sterman,et al.  The impact of endogenous demand on push–pull production systems , 2005 .

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

[20]  Gregory A. DeCroix,et al.  Make-to-order versus make-to-stock in a production-inventory system with general production times , 1998 .

[21]  Ivo J. B. F. Adan,et al.  Combining make to order and make to stock , 1998 .

[22]  Masoud Rabbani,et al.  Capacity coordination in hybrid make-to-stock/make-to-order production environments , 2012 .

[23]  F. Robert Jacobs,et al.  MANUFACTURING PLANNING AND CONTROL SYSTEMS FOR SUPPLY CHAIN MANAGEMENT , 2004 .

[24]  Masoud Rabbani,et al.  Order partitioning and Order Penetration Point location in hybrid Make-To-Stock/Make-To-Order production contexts , 2011, Comput. Ind. Eng..

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