Taguchi Design Of Experiments Pdf

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Taguchi Design Of Experiments Pdf

1.1 What is the Taguchi method and who is Taguchi? 1-1 1.2 Philosophy and a new perspective on quality 1-2 1.3 The new discipline 1-4 1.4 A simpler and more standardized test design method 1-6 1.5 Conference objectives 1-7 Review questions 1-9

Pdf) Use Of Orthogonal Arrays And Design Of Experiments Via Taguchi Methods In Software Testing

2.1 Designing Basics of Experiments 2-1 2.2 2-Level Factorial Experiments 2-4 2.3 Designing Seven-Factor 2-Level Experiments 2-6 2.4 Seven-Factor 2-Level Full Factorial Design 2-7 2.5 Tools for Designing Experiments 2-6 8 2.6 Application steps 2-11 2.7 Test planning procedure

2-13 2.8 Results with multiple evaluation criteria 2-14 2.9 General terms and their definitions 2-15 2.10 Analysis of results 2-17 2.11 Experimental designs with a larger number of factors 2-21 2.12 Design and analysis basic experimental investigation 2-2 2.13 Accuracy of Orthogonal Array Experiments 2-23 2.14 Learning Checklist 2-24

3.1 Experiments designed to study interactions 3-1 3.2 Guidelines for interaction studies 3-5 3.3 Steps in interaction analysis 3-6

4.1 Modification of General Orthogonal Arrays 4-1 4.2 Increasing Column Levels 4-2 4.3 Lowering Columns 4-6 4.4 Incompatible Factor Levels 4-10 4.5 Component Design (Special Technique) 4-11 Course RECAP 4 -1

Pdf) Comparison Design Of Experiment (doe): Taguchi Method And Full Factorial Design In Surface Roughness

5.1 Ambitious Business Goals 5-1 5.2 Mechanics of Outdoor Array Designs 5-3 5.3 Advantages of Outdoor Array Design 5-5 5.4 Analysis of Refined Results 5-6 5.5 MSD Definition for the Three QCs 5 -8 5.6 Test Design and Analysis Strategies 5 -12 5.7 Test Design Tips 5-13

6.1 Analytical Guidelines 6-1 6.2 Testing for the Presence of Interaction 6-5 6.3 ANOVA 6-6 6.4 Conventional Techniques 6-13 6.5 Confidence Intervals of Main Effects 6-15 6.6 Discussion of Some Key Issues 6 -17 6.7 Multiple Runs 8B 6-19 6.8 Example 9A: S/N Analysis – Nominal is Best 6-22 6.9 Example 9B: S/N Analysis – Less is Better 6-24 6.10 Example 9C: S/N Analysis – Bigger Is Better 6 -26 6.11 Understanding and Interpreting Error Terms 6-29

8.1 Description of Application Measures 8-2 8.2 Discussion for Design of Experiments (DOE) 8-3 8.3 Overall Evaluation Criteria 8-5 8.4 Taguchi vs. Classic DOE 8-8

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