Response Surface Methods for Process Optimization (RSM)

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 Mixture Design 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: Experiment Design Made Easy (EDME)
Price includes a $95 fee for workshop materials which is subject to state and local taxes.

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Price: $1,295.00

Response Surface Methods for Process Optimization (RSM)

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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.

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

Design-Expert® software, used in the RSM for Process Optimization workshop, provides the essential computing power for RSM. Several simulations, interspersed throughout the workshop, test knowledge in a realistic fashion. Anderson and Whitcomb's text, "RSM Simplified," is optional.

"Using software helped me gain confidence."
—Bryan Baab, Senior Scientist

Note: If you work with formulations, the Mixture Design workshop may be more appropriate. Call 612-378-9449 and ask to speak with an instructor if you are unsure which workshop to take.

Course Outline

 Day 1  Section 1—Review & Introduction
 
  • Factorial with center points: Case study
  • Introdicing Response Surface Methods (RSM)
  • Augmenting to central composite design (CCD)
   Section 2—Response Surface Methodolog
 
  • “Good” response surface designs
  • Response surface tutorial
  • Details of response surface analysis
 Lunch  Section 3—Building and Analyzing CCDs
 
  • Customized CCDs
  • Model reduction: Exercise
   Section 4—Response Surface Optimization
 
  • Optimization tutorial
    • Numerical
    • Graphical
 Day 2  Section 5—Response Surface Designs
 
  • Box-Behnken designs: Exercise
    • Response transformation: Case study
  • Face-centered CCD (FCD)
    • Design evaluation
  • Alternative composite designs
    • Minimum run resolution V (MR-5) CCD
 Lunch  Section 6—Optimal Design
 
  • Multiple Linear Constraints (MLC): Case study
    • Optimal designs
    • Sizing RSM designs for precision via FDS
  • Categoric factors: Case study
  • RSM design summary
   Section 7—Optional RSM Tools (as time allows)
 
  • Sizing designs to detect a difference: Case study
  • User-defined candidate set: Case study
  • Design augmentation: Case study
  • MLCs revisited: Case study
   Section 8—Homework and DOE Support
 
  • Homework
  • DOE support

Prerequisites

Knowledge of factorial designs, covered in the Experiment Design Made Easy workshop or the "DOE Simplified" book, is a prerequisite.

Additional Information

CEU 1.6
Additional Information No
Recommended Texts and Software

Recommended Texts and Software

Purchase the "RSM Simplified" text or Design-Expert 9 software at the time of registration to receive a 20% discount.