Using an Intelligent Approach to Recognize a Wafer Bin Map Pattern

To decrease cost, semiconductor manufacturing companies always aim for yield enhancement. The analysis of Wafer Bin Maps (WBMs) is important for yield improvement. Real data sets are collected from a famous semiconductor manufacturing company to verify the presented method. Four types of WBMs patterns, center, edge, local, and ring types are selected for verification. Experimental results showed that with adequate parameter settings, the method can successfully recognize the pattern types and distinguish between random and systematic WBMs. There were 17 testing samples, and 16 of them were recognized correctly. The accuracy was 94.12%.