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整合資料挖礦和時間序列以分析半導體製造執行系統和事故預測及分類系統資料以提升綜合使用效益之研究
Thesis

整合資料挖礦和時間序列以分析半導體製造執行系統和事故預測及分類系統資料以提升綜合使用效益之研究

Alejandra Campero Diaz
Masters, 國立清華大學, 工業工程與工程管理學系
2007

Abstract

Overall usage effectiveness Data mining Decision tree Clustering Time series Indirect material usage Semiconductor manufacturing
Wafer fabrication is a complex, costly and lengthy process that involves hundreds of process steps with monitoring of the corresponding process parameters at the same time to enhance the yield. Large amount of data is automatically collected during these processes in wafer fabrication facility. Thus, potential useful information can be extracted from huge data sources to enhance decision quality and enhance operational effectiveness. This study aims to develop a framework to integrate FDC and MES data and then propose an approach based on data mining and time series techniques to investigate the data in order to enhance the overall usage effectiveness (OUE) for cost reduction. We validated this approach with an empirical study in a semiconductor company in Taiwan and the results demonstrated the practical viability of this approach. The extracted information and knowledge is helpful to engineers for identifying the major tools factors affecting indirect material usage effectiveness as well as for indentify periods of time when a specific tool is working using either low or high quantity of material.

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