An adaptive run-to-run optimizing controller for linear and nonlinear semiconductor processes

This paper presents a new run-to-run (R2R) multiple-input-multiple-output controller for semiconductor manufacturing processes. The controller, termed optimizing adaptive quality controller (OAQC), can act both as an optimizer-in case equipment models are not available-or as a controller for given models. The main components of the OAQC are shown and a study of its performance is presented. The controller allows to specify input and output constraints and weights, and input resolutions. A multivariate control chart can he applied either as a deadband on the controller or simply to provide out of control alarms. Experimental designs can be utilized for on-line (recursive) model identification in the optimization phase. For testing purposes, two chemical mechanical planarization processes were simulated based on real equipment models. It is shown that the OAQC allows to keep adequate control even if the input-output transfer function is severely nonlinear. Software implementation including the integration of the OAQC with the University of Michigan's Generic Cell Controller (GCC) is briefly discussed.