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Authors
Schwartz, Jay D.; Rivera, Daniel E.

Digital Object Identifier (DOI)
10.3182/20090706-3-FR-2004.00160

Page Numbers:
964-969

Index Terms
Other; Hybrid and Distributed System Identification; Nonlinear System Identification

Abstract
Efficient supply chain management is a crucial imperative for modern, global enterprises. Tactical decision policies based on process control principles have been developed in the literature for managing production-inventory systems and supply chain networks. To be effective these decision policies depend on accurate nominal models. With a discrete-event simulation acting as a "truth model,'' we employ system identification techniques to parameterize a nonlinear Partial Differential Equation (PDE) model of the semiconductor manufacturing process. A case study shows that the identified PDE model can accurately predict the output of the discrete-event simulation, but without the high computational burden.

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