An Accurate Hybrid - Similarity Technique for User - Defined Wafer Fail - Map Pattern Detection
نویسندگان
چکیده
Abstract—A Hybrid-Similarity technique is proposed for improving the matching accuracy in wafer fail-map pattern detection compared with Cosine-Similarity and Jaccard-Similarity. This is good for gathering the failure data in engineer pre-defined patterns. The adapted low pass filtering and cutting-off technique make the matching calculation simpler and faster than conventional methods. From 5 kinds of typical fail bin maps, this Hybrid-Similarity technique has achieved 87.21% of accuracy which is 8.85% and 17.57% higher than Cosine-Similarity and Jaccard-Similarity, respectively. Execution time of Hybrid-Similarity is 4.05 milliseconds that is 250 times faster than technique of Neural Network.
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