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Unformatted text preview: Cycle Time Prediction for Semiconductor Manufacturing via Simulation on Demand Bruce Ankenman Barry L. Nelson Mustafa Tongarlak Northwestern University John Fowler Gerald Mackulak Detlef Pabst Arizona State University Feng Yang West Virginia University December 21, 2007 Abstract Traditionally, competition between semiconductor manufacturers has primarily fo- cused on product design and cost. Recently, speed of delivery has also become an important differentiator among these firms which has led to manufacturing cycle time becoming a critical performance measure. This paper presents a methodology that performs a limited set of simulation runs for a complex wafer fabrication system and then uses the results to develop metamodels that predict mean steady-state cycle time as a function of product mix and throughput. These predictions can be made on de- mand, i.e., without performing any additional simulation runs, for product mixes and throughput levels not previously simulated. The goal is to support medium and long- range planning by providing results with the fidelity of a detailed simulation model but with the speed of a queueing approximation or simple capacity model. 1 1 Introduction Planning for semiconductor manufacturing, either at the factory or enterprise level, requires answering a large number of what-if questions involving different scenarios for product mix, production targets and capital expansion. A key performance measure for evaluating these scenarios is the time. Accurate cycle-time estimation results in a more stable production environment (Chung and Lai 2006). Shorter cycle times may also lead to in the production of a higher quality product and improved responsiveness to customer needs (Hopp and Spearman 2000). Leachman (2002) indicated that “there is considerable evidence that yields are inversely related to manufacturing cycle times.” The importance of cycle time to the semiconductor manufacturing industry is reinforced within the International Roadmap for Semiconductors 2006 Update (Semiconductor Industry Association, 2006); it states that the improvement of cycle-time targets must be met to prevent slowing of the industry’s growth. Cycle-time reduction is listed in the road map as a difficult challenge for both the near term and the long term. Nemoto et al. (2000) demonstrate that significant financial benefits come from cycle-time reduction in the ramp- up phases of semiconductor manufacturing. Boebel and Ruelle (1996) and Pfund et al. (2006) also indicate that cycle time has become a key performance metric for semiconductor manufacturers. The importance given to cycle time as a performance metric in the semiconductor manu- facturing industry motivates the need for a quick and accurate way to estimate it. A typical factory must constantly review how proposed changes to product mix, start rates, and pro- cess routings will impact the cycle time of both in-process and planned future production....
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This note was uploaded on 04/11/2011 for the course ECE 357 taught by Professor Subjolly during the Spring '11 term at National University of Ireland, Galway.
- Spring '11