Segmental Semi-Markov Models for Endpoint Detection in Plasma Etching
نویسنده
چکیده
We investigate two statistical-detection problems, change-point detection and pattern matching in plasma etch endpoint detection. Our approach is based on a segmental semi-Markov model framework. In the change-point detection problem, the changepoint corresponds to state switching in the model. For pattern matching, the pattern is approximated as a sequence of linear segments which are then modeled as segments (states) in the model. The segmental semi-Markov model is an extension of the standard hidden Markov model (HMM), from which learning and inference algorithms are extended to solve the problems of change-point detection and pattern matching in a principled manner. Results on both simulated and real data from semiconductor manufacturing illustrate the flexibility and accuracy of the proposed framework.
منابع مشابه
Hidden Markov Models for Endpoint Detection in Plasma Etch Processes
We investigate two statistical detection problems in plasma etch endpoint detection: change-point detection and pattern matching. Our approach is based on a segmental semi-Markov model framework. In the change-point detection problem, the change-point corresponds to state switching in the model. For pattern matching, the pattern is approximated as a sequence of linear segments that are modeled ...
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