Scalable Enterprise Systems: A Modular, Scalable Approach to Modeling and Analysis of Semiconductor Manufacturing Supply Chains

Arizona State University, Scottsdale AZ

Investigators

Abstract

The semiconductor manufacturing supply chain is very complex spanning multiple manufacturing sites in various locations around the globe. This grant provides funding that will allow the multidisciplinary research team to use experience gained in factory control to develop control regimes for semiconductor supply chains. The goal is to efficiently and effectively a) model and simulate the physical entities, b) model and simulate the range of decision algorithms, and c) interface the two. The research team has taken a first step toward this. To depict the physical system a basic module was developed that could be used to represent a factory, a transportation link, or a warehouse. The basic module is made up of capacity and delay sub-modules. A supply chain is modeled by connecting basic modules together in series or parallel. This approach provides reasonable execution times while still capturing the qualitative behavior of these systems. Therefore, the research team will first determine reasonable ways to parameterize the basic module. Next, software architectures to support the modeling and analysis of semiconductor supply chains and ensure scalability will be investigated. Real semiconductor supply chain problems (supplied by the industrial participants) will be used in addressing both the parameterization and architecture issues. Finally, how the approach can be implemented in next-generation ERP systems will be studied. If successful, this research will have an impact on the System Architecture of next-generation ERP systems by determining how to include scalable "what-if" capabilities in these systems. It will also facilitate Collaborative Decision Making in scalable enterprise systems by allowing one group of people to describe the way their factories work and another group of people to specify enterprise decision policies. Finally, it will allow for the analysis of various Supply Chain Design issues by providing new modeling and analysis capabilities.