A general equipment diagnostic system and its application on photolithographic sequences

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 unconditional fault probabilities and their bounds are calculated. 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.