Taguchi Methods for Robust Design,9780791801574

Taguchi Methods for Robust Design

by ;
ISBN13: 9780791801574
ISBN10: 0791801578
Format: Hardcover
Pub. Date: 2000-06-01
Publisher(s): Amer Society of Mechanical
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Table of Contents

List of Figures
xi
List of Tables
xiii
Foreword xvii
Preface xix
Introduction
What is Quality Engineering?
1(2)
Quality Engineering and Experimental Design
3(2)
Interactions and Orthogonal Arrays
5(4)
Robust Technology Development
9(4)
What is a Signal-to-Noise Ratio?
13(1)
Where Can SN Ratios Be Used?
14(3)
Concept of SN Ratios
17(2)
Benefits of Using SN Ratios
19(4)
Inverse Proportionality to the Loss Function
20(1)
Simplification of Direct Product Design
20(1)
Simplifies Attainment of Robust Design
20(1)
Simplification of Adjustments or Calibrations
21(1)
Efficient Evaluations for Measuring Systems
21(1)
Reduction of Product-Development Cycle Time
22(1)
Research Applies to a Group of Products (Robust Technology Development)
22(1)
Simple Examples
23(5)
An Example of a Measurement System
23(2)
An Example of an Extrusion Process
25(3)
Parameter Design
28(5)
Layout of Orthogonal Arrays for Parameter Design
33(6)
Types of SN Ratios
Introduction
39(1)
Classification Based on the Type of Data
39(2)
Attribute-Type Data is not Fully Informative
40(1)
Attribute-Type Data is Inefficient
40(1)
Using Attribute-Type Data may Lead to Interactions
40(1)
Classification Based on Intention
41(2)
Classification Based on Input and Output
43(1)
Other Ways of Classifying SN Ratios
43(1)
How to Select SN Ratios
44(2)
Ideal Function
46(3)
Basic Dynamic-Type SN Ratios for Continuous Variables
Introduction
49(1)
Zero-Point Proportional Equation
49(5)
Reference-Point Proportional Equation
54(5)
Linear Equation
59(6)
Linear Equation Using a Tabular Display of the Orthogonal Polynomial Equation
65(4)
Numerically Controlled (NC) Machine Processing
69(28)
Introduction
69(2)
Experiment and Analysis Using Signal-to-Noise Ratio
71(5)
Interpretation and Prediction
76(1)
The Confirmation Run
77(20)
Various Cases
Estimation of Noise
97(4)
Case with an Adjustment Factor
101(12)
Case (I) With Double Signals
113(5)
Case (II) With Double Signals
118(4)
Case When Signal-Factor Levels are Different at Different Runs of an Orthogonal Array
122(2)
Split-Type Analysis
124(13)
What is Split-Type Analysis?
124(1)
Split-Type Analysis for Two-Level Orthogonal Arrays
125(7)
Split-Type Analysis for Mixed-Type Orthogonal Arrays
132(5)
Custom-Written SN Ratios
137(10)
Chemical Reaction I
137(2)
Chemical Reaction II
139(1)
Dynamic Operating Window
140(6)
Optimization of Performance
146(1)
Case When True Values of Signal Factor are Unknown
147(16)
Case When Level Interval of Signal Factor is Known
147(6)
Case When Level Ratio is Known
153(5)
Case When Signal-Factor Variance is Used
158(5)
Nondynamic SN Ratios
Introduction
163(4)
Nominal-is-Best Application
167(8)
Case 1: Non-Negative Data
168(5)
Case 2: Positive and Negative Data
173(2)
Smaller-is-Better Application
175(1)
Larger-is-Better Application
176(1)
Nondynamic Operating Window
177(10)
Classified Attributes
Difference Between Continuous Variables and Classified Attributes
187(4)
Wasted Information
187(1)
Inefficiency
188(1)
Interactions
188(3)
What are the Strategies to Avoid Interactions?
191(1)
Case With Two Classes, One Type of Mistake
192(4)
Case With Two Classes, Two Types of Mistakes
196(11)
Examples
196(4)
Determination of the Standard Rate of Mistakes
200(1)
Standard SN Ratio
201(5)
Comparison of Screening Machines
206(1)
Air-Separation Process
207(4)
Case With Two Classes Where True Values of Signal Factors are Unknown
211(3)
Case With Three or More Classes Where True Values of Signal Factors are Known
214(5)
Equations for Calculation
214(2)
Beer-Taste Recognition
216(3)
Case With Three or More Classes Where True Values of Signal Factors are Unknown
219(4)
Case With Three or More Classes Without a Signal Factor (Classes Have an Order)
223(2)
SN Ratio With Complex Numbers
The Ideal Function of Electric Circuits
225(1)
SN Ratio for Complex Numbers
226(4)
The Hermitian Form
230(6)
Development of a Filter Circuit
236(15)
Explanation of the System
236(1)
The Ideal Function
237(1)
Target Frequency Characteristic
238(1)
Factors, Levels, and Layout
238(3)
Calculation
241(4)
Optimum Condition and Estimation
245(1)
Tuning
246(5)
Layout and Analysis of Youden Squares
Purpose of Using Youden Squares
251(2)
Calculation of Main Effects
253(2)
Numerical Example
255(3)
Derivation
258(3)
Incomplete Data
Introduction
261(2)
Treatment of Incomplete Data
263(4)
Sequential Approximation
267(4)
Procedures
267(1)
Numerical Example
267(4)
Robust Technology Development
Introduction
271(1)
Examples
272(1)
Development of Hardness Standards
272(1)
Development of a Braking System
272(1)
Development of Ammunition
273(1)
Paradigm Shift Needed: Development of Quality Must Begin in R&D
273(1)
How Robust Technology Development Works: The Main Concepts
274(7)
Two-Step Optimization: Reduce Variability First, Then Place on Target
274(1)
Choice of Right Output to Measure
275(1)
To Get Quality, Don't Measure Quality!
276(1)
Energy Transformation and Definition of Ideal Function
277(3)
SN Ratio
280(1)
Advantages of Using Robust Technology Development
281(2)
Technology Readiness
281(1)
Flexibility
282(1)
Reproducibility
283(1)
How Far Advanced is Robust Technology Development?
283(2)
Case Studies
Introduction
285(1)
Mechanical Industry
286(16)
Electrical Industry
302(9)
Chemical Industry
311(6)
Glossary
317(10)
References
327(4)
Index
331(4)
Biographies
Yuin Wu
335(1)
Alan Wu
336

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