Data Analytics and Stochastic Modeling in a Semiconductor Fab

The scale, scope and complexity of the manufacturing operations in a semiconductor fab provide some unique challenges in ensuring product quality and production efficiency. We describe various analytical techniques, based on data mining, process trace data analysis, stochastic simulation and production optimization, that have been used to address these manufacturing issues, motivated by the following two objectives. The first objective is to identify sub-optimal process conditions or tool settings, that potentially affect the process performance and product quality. The second objective is to improve the overall production efficiency through better planning and resource scheduling, in an environment where the product mix and process flow requirements are complex and constantly changing.

By: Sugato Bagchi, Robert J. Baseman, Andrew Davenport, Ramesh Natarajan, Noam Slonim, Sholom Weiss

Published in: RC24895 in 2009


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