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DOE: Screening Experiments Course Outline -- 3 Units

Unit 1 Background for DOE
Lesson 1: Why DOE?
· Limitations of OATs (one-at-a-time) experimentation.
· How designed experiments overcome the limitations of OATs and are a more effective and efficient way to characterize and improve processes and products.
Lesson 2: DOE Terminology
· An explanation of the key terms used in designed experiments.
Lesson 3: Types of Designed Experiments
· Full Factorials.
· Fractional Factorials.
· Screening Experiments.
· Response Surface Analysis.
· EVOP.
· Mixture Experiments.
Lesson 4: Tests of Significance
· Alpha and Beta Risks.
· Degrees of Freedom.
· Hypothesis Tests.
· t-Tests.
· F-Tests.
Lesson 5: Setting Up a Designed Experiment
· Design & Communicate the Objective.
· Define the Process.
· Select a Response and Measurement System.
· Select Factors to be Studied.
· Select the Experimental Design.
· Set Factor Levels.
· Final Design Considerations.
Challenge: An assessment of the learner's progress in this unit.

Unit 2 - Plackett-Burman Experiments
Lesson 1: Plackett-Burman Matrices
· The derivation of Plackett-Burman designs.
· Types of Plackett-Burman matrices.
· Ways to determine the experimental error.
· Techniques for analyzing experimental results.
Lesson 2: Calculating Statistical Significance
· Multiple techniques for testing the statistical significance of factor effects.
· Using graphical techniques to analyze responses and interactions.
Lesson 3: Calculating a Prediction Equation
· Developing a prediction equation using factor effects.
· Using the prediction equation to optimize the process or product.
Lesson 4: Analyzing for the Effect on Variation
· How to analyze variation as a response.
· Creating a scree diagram to graphically analyze factor effects on variation.
Lesson 5: When Bad Things Happen to Good Experiments
· The need for good planning to prevent problems.
· Some techniques for salvaging an experiment if data are lost or suspect.
Challenge: An assessment of the learner's progress in this unit.

Unit 3 - Taguchi Techniques
Lesson 1: Taguchi Concepts
· The concept of robustness.
· The Taguchi Loss Function.
· Signal to noise ratios.
Lesson 2: Taguchi Matrices
· Taguchi designs for two-level experiments.
· Use of Taguchi Interaction Tables.
Lesson 3: Taguchi Experimental Analysis
· Multiple techniques for testing the statistical significance of factor effects.
· Using graphical techniques to analyze responses and interactions.
Lesson 4: Determining Where to Set Factors
· Developing a prediction equation.
· Use the mean, signal to noise ratio, and variation effects to determine where to set factors.
Lesson 5: When Bad Things Happen to Good Experiments
· The need for good planning to prevent problems.
· Some techniques for salvaging an experiment if data are lost or suspect.
Challenge: An assessment of the learner's progress in this unit.