SPC for Machine Particle Counts in Semiconductor Manufacturing

• Main Authors: Yung-Wei Liu, 柳永偉
• Other Authors: Chao-Ton Su
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/85827208403407646684

碩士 === 國立交通大學 === 工業工程與管理系 === 91 === With increasing competition in the semiconductor industry, semiconductor manufacturers are making efforts to increase their productivity. The yield on each wafer is an important index to evaluate productivity. To enhance the yield of IC products, statistical process control (SPC) is the most useful tool in semiconductor manufacturing. The c-chart of SPC has traditionally been used to monitor machine particle counts, thereby controlling the machine condition. However, the clustering phenomenons and unknown factors cause the Possion based c-chart invalid. This study combines data transformation and Neyman distribution to develop a control procedure to monitor machine condition. A case study from a semiconductor company in Taiwan is demonstrated to verify the effectiveness of this proposed method.