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
LIMITED DISTRIBUTION NOTICE:
This Research Report is available. This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). I have read and understand this notice and am a member of the scientific community outside or inside of IBM seeking a single copy only.
Questions about this service can be mailed to reports@us.ibm.com .