A New Morphology-based Approach for Similarity Searching on Wafer Bin Maps in Semiconductor Manufacturing

• Main Authors: Huang, Yu-Syuan, 黃玉宣
• Other Authors: Liao, Chung-Shou
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/35181359269387971046

碩士 === 國立清華大學 === 工業工程與工程管理學系 === 100 === Due to the ever greater complexity of processes involved in semiconductor manufacturing, increasingly high inspection costs associated with defective wafers have become a critical concern of modern manufacturers. More importantly, because current high-dimensional wafer bin maps (WBMs) cause many variations in features, it is difficult to capture the variations of each dimension via traditional pattern recognition or classification methods. Therefore, this work proposes a novel similarity searching tool, a morphology-based support vector machine (MSVM) designed for defective wafer detection. Seven kinds of morphology-based training sample generations are presented; the morphological method includes original morphology definitions in addition to our proposed features. The MSVM can categorize practical industrial datasets according to variant degrees of similarities. The experimental results demonstrate the usefulness of our approach in the context of yield improvements in precision, low errors and acceptable computation cost.