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Because high-dimensional wafer bin maps (WBMs) cause various features, it is difficult to search the similarity among WBMs via conventional pattern recognition methods. This study develops a novel morphology-based support vector machine for defective wafer detection. The experimental results demonstrate its usefulness in yield improvements on precision and computation cost.
Due to increases in the complexity of processes involved in semiconductor manufacturing, increasingly high inspection costs associated with defective wafers has become a critical concern of modern manufacturers. More importantly, because of high-dimensional wafer bin maps (WBMs), it is difficult to capture the variations of each dimension via traditional pattern recognition or classification methods...
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