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Creators/Authors contains: "Yang, Min Jian"

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  1. ; ; (, IEEE)
    Free, publicly-accessible full text available November 3, 2025
  2. ; ; ; (, IEEE)
    Full Text Available 
  3. ; ; (, 2022 IEEE International Test Conference (ITC))
    In the context of analyzing wafer maps, we present a novel approach to enable analytics to be driven by user queries. The analytic context includes two aspects: (1) grouping wafer maps based on their failure patterns and (2) for a failure pattern found at wafer probe, checking to see whether there is a correlation to the result from the final test (feedforward) and to the result from the E-test (feedback). We introduce language driven analytics and show how a formal language model in the backend can enable natural language queries in the frontend. The approach is applied to analyze test data from a recent product line, with interesting findings highlighted to explain the approach and its use. 
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  4. ; ; (, 2022 IEEE International Test Conference in Asia (ITC-Asia))
    We present a novel approach where wafer map pattern analytics are driven by natural language queries. At the core is a semantic parser that translates a user query into a meaning representation comprising instructions to generate a summary plot. The allowable plot types are pre-defined which serve as an interface that communicates user intents to the analytics software backend. Application results on wafer maps from a recent production line are presented to explain the capabilities and benefits of the proposed approach. 
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