Modelling the effect of custom and stock orders on supply-chain performance

Abstract

We model a manufacturer–manufacturer supply chain producing a custom, termed make-to-order (MTO) product, and a stock, termed make-to-stock (MTS) product. The key parameters considered by the model are correlations in the MTO and MTS demand processes, the relative proportion of the MTO demands, production planning strategy by facility, the length of time in advance of production that the schedule must be frozen for each facility, transportation lead time and delays in the transmission of information. Supply-chain performance is measured by production variability and the amount of safety stock required to satisfy a fixed fill rate. The results of the analysis underscore the criticality of taking an integrated view of demand management, production planning, transportation service selection and information flow across the supply-chain.

Keywords:

• Mass customization
• logistics
• production planning

Acknowledgements

This research was supported by the National Science Foundation under Grant No. 9702561 and General Motors. This support is gratefully acknowledged but implies no endorsement of the findings.

June Ma is a Research Associate in the School of Civil and Environmental Engineering at Cornell University. She received the PhD degree in the Department of Civil and Environmental Engineering at Penn State University. Her research interests include system optimization, production planning, and statistical analysis.

Linda K. Nozick received a BSE in Systems Engineering from George Washington University in 1989 and a MS and PhD in Systems Engineering from the University of Pennsylvania in 1990 and 1992 respectively. Currently, she is a Professor in the School of Civil and Environmental Engineering at Cornell University. Her research interests are in the development of mathematical models for use in the management of complex systems. She received a Presidential Early Career Award from the National Science Foundation and the White House in 1997.

Jeffrey D. Tew is GM Technical Fellow and Group Manager of the Manufacturing Enterprise Modeling Group in the Manufacturing Systems Research Lab at General Motor's Research and Development Center in Warren, MI. Currently, Dr. Tew is an Adjunct Professor of Supply Chain Management at Georgia Tech University and a Visiting Professor of Industrial Engineering at Tsinghua University in Beijing. He received a B.S. in mathematics from Purdue University in 1979, a M.S. in statistics from Purdue University in 1981, and a Ph.D. in industrial engineering from Purdue University in 1986.

Lynn T. Truss is a Staff Research Scientist in the Manufacturing Systems Research Lab at General Motors R&D Center in Warren, Michigan. She is currently managing the Enterprise Demand Management Research Program, which focuses on manufacturing enterprise demand modeling using online and offline data. Lynn received a BS in Mathematics from the State University of New York at Albany in 1982, and an MA in Statistics from Yale University in 1983.

Theodore Costy is a research scientist at General Motors Corporation. He has an MS in management of technology from Renssellaer Polytechnic Institute, an MA in computer science from Wayne State University, and a BS in mathematics and computer science form Wayne State University. His research interests include decision support tools and supply chain management.