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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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.more » « less
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We present a novel approach called MINiature Interactive Offset Networks (or MINIONs). We use wafer map classification as an application example. A Minion is trained with a specially-designed one-shot learning scheme. A collection of Minions can be used to patch a master model. Experiment results are provided to explain the potential areas Minions can help and their unique benefits.more » « less
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null (Ed.)In this work, we consider learning a wafer plot recognizer where only one training sample is available. We introduce an approach called Manifestation Learning to enable the learning. The underlying technology utilizes the Variational AutoEncoder (VAE) approach to construct a so-called Manifestation Space. The training sample is projected into this space and the recognition is achieved through a pre-trained model in the space. Using wafer probe test data from an automotive product line, this paper explains the learning approach, its feasibility and limitation.more » « less
