Award Abstract #0107666
IGMS: Optimizing Supply Networks and Re-Entrant Manufacturing Systems in the Semiconductor Industry

NSF Org:	DMS Division of Mathematical Sciences
Initial Amendment Date:	February 28, 2002
Latest Amendment Date:	February 28, 2002
Award Number:	0107666
Award Instrument:	Standard Grant
Program Manager:	Lloyd E. Douglas DMS Division of Mathematical Sciences MPS Directorate for Mathematical & Physical Sciences
Start Date:	March 1, 2002
Expires:	August 31, 2003 (Estimated)
Awarded Amount to Date:	$99945
Investigator(s):	Matthias Kawski kawski@asu.edu (Principal Investigator) Peter Crouch (Co-Principal Investigator)
Sponsor:	Arizona State University ORSPA TEMPE, AZ 85287 480/965-5479
NSF Program(s):	INFRASTRUCTURE PROGRAM, OFFICE OF MULTIDISCIPLINARY AC
Field Application(s):	0000099 Other Applications NEC
Program Reference Code(s):	OTHR, 0000
Program Element Code(s):	1260, 1253

ABSTRACT

The PI will perform research on supply networks and scheduling of re-entrant manufacturing systems while in residence in the Technology and Manufacturing Group at INTEL Corporation. While transferring theoretical results and paradigms of nonlinear control into large scale industrial applications, a major objective is to develop in-depth knowledge of the practical needs, constraints, and objectives of industrial operations, sufficient for effective future collaborations with representatives from industry, business, and industrial engineering faculty, and to optimally prepare future undergraduate and graduate students.

The technical focus is on problems of immediate interest to the semi-conductor industry. As a roughly $100B business in the US alone, this industry is characterized by capital intensive manufacturing plants and

short product life-cycles. Together with rapidly changing demands and prices, this framework promises a particularly high return on investments to optimize operations. The first problem is to optimize the management of the global supply networks of the semiconductor industry. This includes phasing in/out changing products, using facilities that are distributed around the globe, avoiding overproduction and hedging against fluctuations in demand and production. A key objective is to connect commonly used financial with optimal control. The second problem is to optimize the scheduling of re-entrant manufacturing systems. A major theoretical problem is to formulate an analogue of the dynamic programming paradigm for such systems without a distinguished direction of signal flow.

This project will immediately impact the many courses taught and seminar series organized by the PI. He will also quickly communicate his insights to the larger communities in mathematical control and undergraduate

education. This IGMS project is jointly supported by the MPS Office of Multidisciplinary Activities (OMA) and the Division of Mathematical Sciences (DMS).

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