Discovery of Resource-Oriented Transition Systems for Yield Enhancement in Semiconductor Manufacturing
| Autor: | Byeong-Eon Lee, Euiseok Kum, Gyunam Park, Jinyoun Lee, Minsu Cho, Minseok Song |
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| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Process (engineering) Semiconductor device fabrication Computer science Yield (finance) 02 engineering and technology Work in process Condensed Matter Physics Industrial engineering Industrial and Manufacturing Engineering Electronic Optical and Magnetic Materials 020901 industrial engineering & automation Resource (project management) Empirical research Yield management Performance indicator Electrical and Electronic Engineering |
| Zdroj: | IEEE Transactions on Semiconductor Manufacturing. 34:17-24 |
| ISSN: | 1558-2345 0894-6507 |
| Popis: | In semiconductor manufacturing, data-driven methodologies have enabled the resolution of various issues, particularly yield management and enhancement. Yield, one of the crucial key performance indicators in semiconductor manufacturing, is mostly affected by production resources, i.e., equipment involved in the process. There is a lot of research on finding the correlation between yield and the status of resources. However, in general, multiple resources are engaged in production processes, which may cause multicollinearity among resources. Therefore, it is important to discover resource paths that are positively or negatively associated with yield. This article proposes a systematic methodology for discovering a resource-oriented transition system model in a semiconductor manufacturing process to identify resource paths resulting in high and low yield. The proposed method is based on the model-based analysis (i.e., finite state machine mining) in process mining and statistical analyses. We conducted an empirical study with real-life data from one of the leading semiconductor manufacturing companies to validate the proposed approach. |
| Databáze: | OpenAIRE |
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