Response Surface Methods (RSM) for Peak Process Performance at the Most Robust Operating Conditions

Response surface methods (RSM) provide superb statistical tools for design and analysis of experiments aimed at process optimization. At the final stages of process development, RSM illuminates the sweet spot where high yield of in-specification products can be achieved at lowest possible cost. It produces statistically-validated predictive models and, with the aid of specialized software, response surface maps that point the way to pinnacles of process performance. This article starts with the basics on RSM before introducing two enhancements that focus on robust operating conditions: • Modeling the process variance as a function of the input factors • Propagation of error (POE) transmitted from input factor variation. Putting all these tools together, the process engineer can find the find the flats – high plateaus for maximum yield and broad valleys that minimize defects.