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.
This course is part of the Design of Experiments Specialization
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Design of Experiments SpecializationArizona State UniversityAbout this Course
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Course 3 of 4 in the
Intermediate Level
Approx. 13 hours to complete
English
Subtitles: French, Portuguese (European), Russian, English, Spanish
What you will 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
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 3 of 4 in the
Intermediate Level
Approx. 13 hours to complete
English
Subtitles: French, Portuguese (European), Russian, English, Spanish
Offered by
Arizona State University
Arizona State University has developed a new model for the American Research University, creating an institution that is committed to excellence, access and impact. ASU measures itself by those it includes, not by those it excludes. ASU pursues research that contributes to the public good, and ASU assumes major responsibility for the economic, social and cultural vitality of the communities that surround it.
Syllabus - What you will learn from this course
5 hours to complete
Unit 1: Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs
5 hours to complete
12 videos (Total 125 min), 4 readings, 3 quizzes
2 hours to complete
Unit 2: Regression Models
2 hours to complete
7 videos (Total 98 min), 1 reading, 2 quizzes
4 hours to complete
Unit 3: Response Surface Methods and Designs
4 hours to complete
14 videos (Total 178 min), 1 reading, 2 quizzes
2 hours to complete
Unit 4: Robust Parameter Design and Process Robustness Studies
2 hours to complete
4 videos (Total 39 min), 1 reading, 2 quizzes
Reviews
TOP REVIEWS FROM RESPONSE SURFACES, MIXTURES, AND MODEL BUILDING
by AZOct 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.
by RRJul 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.
About the Design of Experiments Specialization
Learn modern experimental strategy, including factorial and fractional factorial experimental designs, designs for screening many factors, designs for optimization experiments, and designs for complex experiments such as those with hard-to-change factors and unusual responses. There is thorough coverage of modern data analysis techniques for experimental design, including software. Applications include electronics and semiconductors, automotive and aerospace, chemical and process industries, pharmaceutical and bio-pharm, medical devices, and many others.
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