Dual Response Surface Methods (RSM) to Make Processes More Robust

presented by Mark Anderson

Response surface methods (RSM) provide statistically-validated predictive models, sometimes referred to as "transfer functions," that can then be manipulated for finding optimal process configurations. The dual response approach to RSM captures both the average and standard deviation of the output(s) and simultaneously optimizes for the desired level at minimal variation, thus achieving an on-target, robust process. With inspiration provided by a case study on a semiconductor etching process, the positive repercussions of these methods will be readily apparent, especially for those involved in design for six sigma (DFSS) quality programs.