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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chih-Min Fan Yun-Pei Lu |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Ind. Eng. & Manage., Yuan Ze Univ., Taoyuan, Taiwan (Chih-Min Fan; Yun-Pei Lu) |
| Abstract | This paper studies the issues of designing a Bayesian framework for the reliable diagnosis of various yield-loss factors induced in semiconductor manufacturing. The proposed framework integrates both the results from knowledge-based and data-driven inference tools as input data, where the former resembles expert¿s knowledge on diagnosing pre-known yield-loss factors while the latter serves for exploring new yield-loss factors. Three modules with specific designs for yield diagnosis applications are addressed: pre-process for generating candidate factors and corresponding prior distributions, Bayesian inference for calculating posterior distributions, and post-process for deriving reliable rankings of candidate factors. The final output, a bubble diagram with Pareto frontier, provides visual interpretations on the integral results from data-driven, knowledge-based and Bayesian inference tools. Specific issues addressed in the proposed Bayesian framework provide directions for implementing a real system. |
| Starting Page | 2323 |
| Ending Page | 2329 |
| File Size | 1300006 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781424427079 |
| DOI | 10.1109/WSC.2008.4736337 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-12-07 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Bayesian methods Time to market Diagnostic expert systems Knowledge engineering Semiconductor device manufacture Power engineering and energy Fuzzy neural networks Data engineering Analysis of variance Industrial engineering |
| Content Type | Text |
| Resource Type | Article |
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