Design of Experiments Overview (1:01)
Statistical Thinking for Industrial Problem Solving
A free online statistics course
Design of Experiments
Design of experiments (DOE) is a rigorous methodology that enables scientists and engineers to study the relationship between multiple input variables, or factors, on key output variables, or responses.
In this module, you will learn why designed experiments are better than trial and error and one-factor-at-a-time approaches to gain an understanding of cause and effect relationships and interactions between factors. You will be introduced to several types of designs such as factorial, response surface and custom designs. Finally, you will learn some DOE guidelines and best practices which will help you succeed with experimentation.
Estimated time to complete this module: 3 to 4 hours
Specific topics covered in this module include:
Introduction to DOE
- What is DOE?
- Conducting Ad Hoc and One-Factor-at-a-Time (OFAT) Experiments
- Why Use DOE?
- Terminology of DOE
- Types of Experimental Designs
- Designing Factorial Experiments
- Analyzing a Replicated Full Factorial
- Analyzing an Unreplicated Full Factorial
- Screening for Important Effects
- A Look at Fractional Factorial Designs
- Custom Screening Designs
Response Surface Experiments
- Introduction to Response Surface Designs
- Analyzing Response Surface Experiments
- Creating Custom Response Surface Designs
- Sequential Experimentation
- Introduction to DOE Guidelines
- Defining the Problem and the Objectives
- Identifying the Responses
- Identifying the Factors and Factor Levels
- Identifying Restrictions and Constraints
- Preparing to Conduct the Experiment
- Case Study