Factorial experiments are often used in factor screening.; that is, identify the subset of factors in a process or system that are of primary important to the response. Once the set of important factors are identified interest then usually turns to optimization; that is, what levels of the important factors produce the best values of the response. This course provides design and optimization tools to answer that questions using the response surface framework. Other related topics include design and analysis of computer experiments, experiments with mixtures, and experimental strategies to reduce the effect of uncontrollable factors on unwanted variability in the response.
Response Surfaces, Mixtures, and Model Building
Response Surfaces, Mixtures, and Model Building
This course is part of Design of Experiments Specialization
Instructor: Douglas C. Montgomery
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4.7
(66 reviews)
Intermediate level
Some related experience required
13 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Conduct experiments w/computer models and understand how least squares regression is used to build an empirical model from experimental design data
Understand the response surface methodology strategy to conduct experiments where system optimization is the objective
Recognize how the response surface approach can be used for experiments where the factors are the components of a mixture
Recognize where the objective of the experiment is to minimize the variability transmitted into the response from uncontrollable factors
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Assessments
8 assignments
Taught in English
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This course is part of the Design of Experiments Specialization
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There are 4 modules in this course
What's included
12 videos4 readings2 assignments1 app item1 discussion prompt
What's included
7 videos1 reading2 assignments
What's included
14 videos1 reading2 assignments
What's included
4 videos1 reading2 assignments
Instructor
Instructor ratings
4.8 (25 ratings)Offered by
Recommended if you're interested in Probability and Statistics
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4.7
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AZ
5
Reviewed on Oct 9, 2021
DoE is an essential but forgotten initial step in the experimental work! This course gives a very good start and breaking the ice for higher quality of experimental work.
DR
5
Reviewed on Jul 25, 2020
It was a great experience for me to do the RSM model building an online course. I learned experimental designs for fitting response surfaces.
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