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by Sovarong Leang, Prof Costas Spanos
http://bcam.berkeley.edu/archive/tsm95-leang.pdf
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Abstract:
This paper presents a general diagnostic system that can be applied to semiconductor equipment to assist the operator in finding the causes of decreased machine performance. Based on conventional probability theory, the diagnostic system incorporates both shallow and deep level information. From the observed evidence, and from the conditional probabilities of faults initially supplied by machine experts (and subsequently updated by the system), the fault probabilities and their bounds are calculated, given a specified confidence level. The rate of convergence of the fault probabilities has been derived in detail in the paper, and the procedure for combining the estimates of conditional probabilities given by the machine experts has also been described in detail. We have implemented a software version of the diagnostic system, and tested it on real photolithography equipment malfunctions and performance drifts. Initial experimental results are encouraging. 1
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