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Design of Experiments for Robust Optimization and Tolerance Design

Duration: 1.0 day
CEUs: 0.6
Available for on-site training or can be scheduled at any SAS training facility if demand warrants.

This course is designed for individuals working directly on product and process develelopment to characterize, optimize, and control product and process performance.

Learn how to

Who should attend

Engineers, scientists, and Six Sigma professionals who actively work on any aspect of product and process development where the goal is to improve product and process performance

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Prerequisites
Before attending this course, you should complete an ANOVA and regression course. The recommended prerequisites are JMP Software: Statistical Data Exploration and JMP Software: ANOVA and Regression or Engineering Statistics and Data Analysis for Performance Excellence
Course Contents
Introduction to DOE and Robust Design
Experimental Preparation
Full Factorial Design
Screening Design
  • augment design
Custom Designs
  • generating custom designs
  • evaluating custom designs
  • analysis of custom designs
  • strategies to minimize experimental size
  • adding covariate and uncontrolled factors
  • supersaturated designs
  • split plot designs
  • strip plot designs
  • blocking designs
  • mixtures in custom designs
  • setting constraints in the design
Response Surface Design
Special Topics in DOE (optional)
  • mixture designs
  • evolutionary operations (EVOP)
  • Taguchi arrays
Software
This course addresses JMP.
Course Materials
Students receive a hardcopy of the course notes and, in some courses, can choose to take home a copy of the course data.
Share Your Thoughts
Are there additional topics you'd like for this course to address? Would you like for this course to be offered at another training facility? Let us know by adding to our Interest List.

Not currently scheduled. Available for on-site training or can be scheduled at any SAS training facility if demand warrants.


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