In statistics, response surface methodology (RSM) explores the relationships between several explanatory variables and one or more response variables. SigmaXL - Leading Provider of User Friendly Excel Add-Ins for Statistical and Graphical Analysis. Design and Analysis of Response Surface Experiment. Response Surface Methodology1 CASOS Technical Report Kathleen M. And the Institute for Software Research International at Carnegie Mellon University. Basic approach of response surface methodology. An easy way to estimate a first-degree polynomial model is to use a factorial experiment or a fractional factorial design.

In this 2-day computer-intensive workshop, participants learn how to find optimal operating conditions with response surface methods (RSM). Find the 'sweet spot' where you meet all your specifications at minimal cost. You will learn how to set up central composite, Box-Behnken and other RSM designs, generate 3D and contour maps and optimize multiple responses. Note: If you work with formulations, the workshop may be more appropriate.

Call 612-378-9449 and ask to speak with an instructor if you are unsure which workshop to take. Prerequisite: Price includes a $95 fee for workshop materials which is subject to state and local taxes. A 10% Early Bird discount will be applied to registrations made 6 weeks prior to the workshop date. Response Surface Methods for Process Optimization (RSM) (2 days) Achieve Peak Performance Response Surface Methods (RSM) can lead you to the peak of process performance. The RSM for Process Optimization workshop teaches you how to produce precise maps based on statistical models. Recycle No Cd Patch.

Learn how to put all your responses together via sophisticated optimization approaches. Find the 'sweet spot' where you meet all specifications at minimal cost. Learn Sophisticated Statistical Methods During the RSM for Process Optimization workshop you will learn how to: • Set up central composite (CCD), Box-Behnken and Optimal RSM designs • Select appropriate regression models • Evaluate design properties • Use FDS curves to adequately size designs • Generate response surface contours • Optimize multiple responses numerically • Add multilinear constraints and categoric factors to optimal designs 'Clearly presented with emphasis on application.' —Dennis Passe, Food Scientist Use Powerful Software to do Case Studies and Simulations software, used in the RSM for Process Optimization workshop, provides the essential computing power for RSM.