Learn how to use response surface methods in Six Sigma projects. Response surface methods (RSM), are a class of experimental designs that allow you to model curvature and second-order or quadratic Y=f(x) relationships.
Response Surface Methods or RSM…are another class of designs…different from factorial designs.…The big advantage that Response Surface Methods have…over factorial designs is that RSM is able…to model curvature and second-order,…or quadratic relationships.…If there is significant curvature,…the factorial designs are not adequate.…You can use RSM designs when there is curvature.…The theoretical basis for RSM…is that an output Y is represented…by a curved response surface.…
A Second-Order or Quadratic Model is required…as shown here where x1 and x2 are the factors of interest.…The difference between a Response Surfaced equation…and a equation for a factorial design…is the addition of the squared or quadratic terms.…These terms are added to model curvature in that response.…There are many designs in RSM.…Central Composite Design, CCD, is the most popular.…
In CCD, all factors have only two levels,…and the centerpoints and axial points are defined.…The main effects and interactions are determined…by cube points, which are comparable…
Author
Richard Chua
Released
5/25/2017LinkedIn Learning (Lynda.com) is a PMI Registered Education Provider. This course qualifies for professional development units (PDUs). To view the activity and PDU details for this course, click here.
The PMI Registered Education Provider logo is a registered mark of the Project Management Institute, Inc. Dr. Richard Chua builds upon his Six Sigma: Green Belt, Six Sigma Foundations, and Learning Minitab courses—which are prerequisites to this course—and covers an array of topics, including measurement system analysis, hypothesis testing, response surface methods, displaying improved process capabilities, and more.
- Process flow metrics
- Measurement system analysis
- Calculating process capability
- Hypothesis testing
- Confidence intervals
- Testing for normality
- Designing, conducting, and analyzing full-factorial experiments
- Using fractional factorial experiments for screening
- Displaying improved process capability
Skill Level Intermediate
Duration
Views
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Introduction
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Welcome1m 38s
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Certification information1m 31s
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Exercise files34s
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1. Define Phase
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Overview of the Define phase3m 51s
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2. Measure Phase
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Process flow metrics3m 34s
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Sample sizes3m 7s
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3. Analyze Phase
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Hypothesis testing road map3m 33s
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Confidence intervals3m 14s
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Test for normality2m 49s
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Compare variances5m 16s
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T-tests6m 4s
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ANOVA3m 55s
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Contingency tables6m 49s
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Nonparametric tests6m 49s
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Correlation3m 45s
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Linear regression4m 38s
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Multiple regression5m 5s
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4. Improve Phase
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Full-factorial experiments9m 19s
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DOE with curvature6m 27s
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Response surface methods8m 37s
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5. Control Phase
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SPC chart selection4m 46s
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SPC chart analysis5m 1s
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Conclusion
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Next steps56s
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Video: Response surface methods