A systematic approach is presented for modeling qualitative properties in semiconductor manufacturing processes. This approach is based on the fuzzy logic theory, and on the statistical analysis of categorical data. A fuzzy inference system can be designed and created by training data obtained either from human expert knowledge, or automatically extracted from statistically designed experiments. Before being used to design the fuzzy system, the data extracted from the designed experiments can be processed and filtered with the help of linear and logistic regression analysis. After the establishment of the initial inference system, the fuzzy membership functions can be tuned adaptively to accommodate process changes.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.