DOE:  Screening Experiments

Outline
Show Course Objectives

Course outline

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

Unit Test

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 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.

Unit Test

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.

Unit Test

Challenge

An assessment of the learner’s progress in this unit.