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DOE:  Screening Experiments

 

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DOE: Screening Experiments Training

 

Course Description

Course Objectives

Intended Audience

Time to Complete

Course Demo

Course Outline

Why Does My Company Need This Program?

Course Description

DOE:  Screening Experiments are the most powerful of Design of Experiments techniques to uncover the power factors in a manufacturing process.  With a small number of experimental runs and very little data your can make significant improvements to processes.  The most common screening experiment techniques - Taguchi and Plackett-Burman techniques are covered in detail in this course.

Course Objectives

Unit 1:  Background for DOE

  • Why design of experiments (DOE) are more efficient and effective than one-at-a-time (OAT) experimentation.

  • What the major terms used in designed experiments mean.

  • Types of designed experiments and when they are best used.

  • How to use basic tests of significance.

  • How to plan a designed experiment.

Unit 2:  Plackett-Burman Techniques

  • How Plackett-Burman designs were derived.

  • How to determine which Plackett-Burman matrix to use for your application.

  • How to estimate the experimental error in Plackett-Burman experiments.

  • How to analyze experimental results and calculate the statistical significance of factor effects.

  • How to develop a prediction equation that can be used to optimize the response.

  • How to salvage experiments if data are lost.

Unit 3:  Taguchi Techniques

  • Why Taguchi techniques focus on the robustness of the product.

  • How the Quality (Taguchi) Loss Function is used.

  • How to calculate and use Signal to Noise ratios.

  • How Taguchi designs were derived.

  • How to determine which Taguchi design to use for your application.

  • How to use Taguchi interaction tables.

  • How to test the statistical significance of factor effects.

  • How to develop a prediction equation that can be used to optimize the response.

  • How to use mean, S/N, and variation effects to determine where to set factors.

  • How to salvage experiments if data are lost.

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Intended Audience

Engineers, supervisors, technical support personnel.

Time To Complete

Five to seven hours.

Course Demo

Design of Experiments: Screening Experiments Training Course Demo

View demo of the DOE: Screening Experiments Course.

Course Outline

This course includes three units:  Background for DOE, Plackett-Burman Techniques, and Taguchi Techniques.

Screening Experiments 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

  • a and b 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

DOE Challenge

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

Unit 2 - Plackett-Burman Techniques

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.

Unit Test

DOE 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

DOE Challenge

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

 

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Why Does My Company Need This Program?

If your company needs to optimize processes, you can't afford to use one-at-a-time experiments because they are costly and miss important interactions that might have a significant effect on the process.  But, learning screening experiment techniques can be costly and involve time away from the job plus travel expenses.  With Screening Experiments, you can learn how to use Taguchi and Plackett-Burman techniques right on your computer.  It's affordable, flexible, and convenient.

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