The Value of Simulation in Modeling Supply Chains

Proceedings of the 1998 Winter Simulation Conference D.J. Medeiros, E.F. Watson, J.S. Carson and M.S. Manivannan, eds.

Ricki G. Ingalls
Manufacturing Strategy Group
Compaq Computer Corporation
20555 SH 249
Houston, TX 77070, U.S.A.

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In business today, re-engineering has taken a great deal of the cost out of internal corporate processes. Our factories and internal support organizations have become much more efficient, but there is still a great deal of unnecessary cost in the overall delivery system, or the supply chain. Although your corporation does not own all of the supply chain, the entire chain is responsible for product delivery and customer satisfaction. As one of several methodologies available for supply chain analysis, simulation has distinct advantages and disadvantages when compared to other analysis methodologies. This paper discusses the reasons why one would want to use simulation as the analysis methodology to evaluate supply chains, its advantages and disadvantages against other analysis methodologies such as optimization, and business scenarios where simulation can find cost reductions that other methodologies would miss.


Business Process Re-engineering (BPR) continues to be a driving force in the improvement of the operations of many large companies. BPR has its basis on a very simple concept, simplify. The idea is that the more simple an organization, the better material and information will flow through the system. This concept has been a driver for companies using some traditional operations research optimization methodologies as they never have before. Especially in the planning and scheduling area, optimization is enjoying a growth that was unimaginable just a decade ago. One simply has to look at the success of i2 Technologies, Manugistics, Aspen Technologies, Chesapeake Decision Sciences (which was recently bought by Aspen), and others who are showing extraordinary growth. i2, perhaps the leader of this group, has seen revenues roughly double every year for the last 5 years.

Yet for all its success, Manugistics acquired Tyecin Systems, a simulation company that has specialized in the simulation and scheduling of semiconductor fabs. Yet in Manugistics press release annoucing the merger, the word simulation was not mentioned. Rather, Manugistics decided to describe Tyecin as "the leading supplier of advanced planning and scheduling applications for the semiconductor industry."

In a similar move, Symix purchased Pritsker Corporation for $9 million. Although Pritsker Corporation has a long history in the area of simulation, Symix said that "the acquisition will make Symix the first enterprise resource planning (ERP) company to bring advanced planning and scheduling (APS) to midsize manufacturers." The meaning is clear. Pritsker Corporation was bought for its simulation-based scheduling software and not it the general purpose simulation software.

What can we make of these acquisitions? For all their success, there are some supply chain and scheduling problems that the large supply chain software companies do not have a good solution for today. This is where simulation comes into play.

Throughout the remainder of this paper, we will discuss the use of optimization and simulation as tools for supply chain analysis. We will also discuss business drivers and scenarios where supply chain analysis is better accomplished using simulation instead of optimization.


2.1 Traditional Supply Chain Analysis

When taking the Production Planning, Scheduling and Inventory Control class at Texas A&M, we went through several fairly complicated multi-stage, multi-plant, multiproduct problems that could accurately be described as a supply chain. In class, the traditional approach was a linear program whose objective was to minimize cost or maximize profit. In some problems, we may have used dynamic programming because the problem had stochastic demand. These problems had to be quite simple, usually single product, single-stage, just to make the problem tractable. Although these were classroom problems, the basic techniques are not much different from the implementation of supply chain algorithms in today's leading software. There may be a mixed-integer formulation of the problem or a "clean-up" algorithm after the optimization is finished to handle difficult rules that the user may put it, but underneath it all, it is still optimization.

While at SEMATECH, we developed the Manufacturing Enterprise Model (MEM). MEM is a global strategic planning tool for the semiconductor industry. Since its development in 1994, MEM has been customized by Motorola and is used throughout their semiconductor business. IBM has also customized MEM for their own use. Except for the time horizon (2 to 5 years instead of minutes or days or weeks), MEM is not unlike the major supply chain analysis products as far as the underlying methodology. To understand the scope of such a system, let me take a section from the MEM User's Manual.