Arizona State University - Response Surfaces, Mixtures, and Model Building
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Response Surfaces, Mixtures, and Model Building at Coursera Overview
Duration | 13 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Response Surfaces, Mixtures, and Model Building at Coursera Highlights
- This Course Plus the Full Specialization.
- Shareable Certificates.
- Graded Programming Assignments.
Response Surfaces, Mixtures, and Model Building at Coursera Course details
- 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 at Coursera Curriculum
Unit 1: Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs
Instructor Introduction
Course Introduction
More About Factorial and Fractional Factorial Designs
The 3^3 Design
The 3^k Factorial Design
Confounding
Fractional Replication of the 3^k Factorial Design
Factorials with Mixed Levels
Nonregular Fractional Factorial Designs
Use of an Optimal Design Tool
Syrup Loss Example
Unusual Blocking Example
Course Description
Course Textbook and Resources
Best Practices in Online Learning (or How to Succeed in This Class)
Unit 1: Introduction
Unit 1: Concept Questions
Exercise 1
Unit 2: Regression Models
Linear Regression Models
Properties of the Estimators
Regression Analysis of a 2^3 Factorial Design
Hypothesis Testing in Multiple Regression
Confidence Intervals in Multiple Regression
Regression Model Diagnostics
Viscosity Example
Unit 2: Introduction
Unit 2: Concept Questions
Exercise 2
Unit 3: Response Surface Methods and Designs
Response Surface Methodology
The Method of Steepest Ascent
Second-Order Models in RSM
Ridge Systems
Multiple Responses
Experimental Designs for Fitting Response Surfaces
Blocking in a Second-Order Design
The Adhesive Pull-Off Force Experiment
General Structure of a Definitive Screening Design with m Factors
Experiments with Computer Models
Mixture Experiments
Constraints
Chemical Process Example
Paint Formulation Example
Unit 3: Introduction
Unit 3: Concept Questions
Exercise 3
Unit 4: Robust Parameter Design and Process Robustness Studies
Robust Design
Analysis of the Crossed Array Design
Combined Array Designs and the Response Model Approach
Semiconductor Manufacturing Example
Unit 4: Introduction
Unit 4: Concept Questions
Exercise 4
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