The goal of our control system is to improve the reliability, accuracy, and economy of operation of a sequence of interrelated processes. We achieve this task by using well known, rigorous statistical techniques to continuously monitor process parameters, detect out-of-control equipment, and then optimally adjust relevant machine inputs to bring the process back on target. We have implemented the supervisory control system on the photolithography sequence in the Berkeley Microfabrication Laboratory, where it has been conclusively proven that the supervisory control system increases significantly the capability of the entire process. The supervisory control algorithms, consisting of feedback and feed-forward control, multivariate, model-based statistical process control (SPC), and automated specification management algorithms, are independent of machine and/or process, and can be applied to any semiconductor manufacturing sequence.