標題: Data transformation in SPC for semiconductor machinery control: A case of monitoring particles
作者: Chen, MC
Su, CT
Hsu, CC
Liu, YW
工業工程與管理學系
Department of Industrial Engineering and Management
關鍵字: machinery control;semiconductor manufacturing;control chart;particle counts
公開日期: 1-七月-2005
摘要: Yield is an important indicator of productivity in semiconductor manufacturing. In the complex manufacturing process, the particles on wafers inevitably cause defects, which may result in chip failure and thus reduce yield. Semiconductor manufacturers initially use wafer testing to control the machine for the number of particles. This machinery control procedure aims to detect any unusual condition of machines, reduce defects in actual wafer production and thus improve yield. In practice, the distribution of particles does not usually follow a Poisson distribution, which causes an overly high rate of false alarms in applying the c-chart. Consequently, the semiconductor machinery cannot be appropriately controlled by the number of particles on machines. This paper primarily combines data transformation with the control chart based on a Neyman type- A distribution to develop a machinery control procedure applicable to semiconductor machinery. The proposed approach monitors the number of particles on the testing wafer of machines. A semiconductor company in Taiwan in the Hsinchu Science Based Industrial Park demonstrated the feasibility of the proposed method through the implementation of several machines. The implementation results indicated that the occurrence of false alarms declined extensively from 20% to 4%.
URI: http://dx.doi.org/10.1080/00207540500070475
http://hdl.handle.net/11536/13519
ISSN: 0020-7543
DOI: 10.1080/00207540500070475
期刊: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Volume: 43
Issue: 13
起始頁: 2759
結束頁: 2773
顯示於類別:期刊論文


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  1. 000229550100006.pdf