應用於半導體製程統計工程管理技術的優化

On the improvement of Statistical Process Management techniques in Semiconductor Fab Processes

廉大植(YEOM DAESIK)

指導教授 ： 曹承礎

國立臺灣大學/管理學院/企業管理碩士專班/碩士(2021年)

https://doi.org/10.6342/NTU202104364

摘要

本論文主要介紹半導體製程和一般性統計工程管理方法應用於半導體製程，為了符合半導體製程在目前晶圓廠的流程，本論文優化了控制流程與能力指數於現有的統計工程管理技術。半導體製程是要求精密裝備和高技術的高科技裝置產業，如果不事先預防製程事故，有可能造成投入製程的所有晶片都無法使用的巨大損失。 本論文介紹了符合半導體製程特點的統計性工程管理方法，從製程事故的事前預防，對於提高質量問題早期檢測力的方法提出建議和持續改善方法。

關鍵字

應用於半導體 ； 統計工程管理技術

並列摘要

The semiconductor is the industry that manufactures integrated circuit (IC) chips with high precision equipment and cutting-edge technology. Manufacturing processes in fabrication plants (FAB) are capital intensive, carrying the costly risk of low line yield – a situation when inputting wafers are not scraped, or used up, entirely. For semiconductor companies to remain profitable and competitive, preventative risk management mechanisms must be embedded in the FAB production processes for quality control. This thesis discusses the statistical process control (SPC) techniques employed at Company S – one of the industry leaders in semiconductors – for early detection of quality problems, focusing on the X bar R control chart to monitor production quality overtime against benchmarked control limits and the process capability indices (Cp, Cpk) to determine process capability in the presence of external factors. The thesis illustrates how Company S strategically deploys its SPC strategy for quality control (QC) to recognize quality problems in advance and lower occurrence rates in the future.

並列關鍵字

tatistical Process Management techniques ； Semiconductor Fab Processes

參考文獻

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