Home
This Title All WIREs
WIREs RSS Feed
How to cite this WIREs title:
WIREs Comp Stat

The Taguchi method

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract Achieving robustness in product and process designs is of importance to various stakeholders such as manufacturers, suppliers, and consumers. As variability exists in all operations, it is desirable to create products and processes that are not very sensitive to factors that are not controllable. The Taguchi method is an approach to robust design. Inherent in the Taguchi method is the definition of a loss function. This loss function formulation is influenced by the type of quality characteristic under consideration, that is, smaller‐is‐better, larger‐is‐better, or target‐is‐best. Furthermore, based on the selected type of quality characteristic, a performance measure is defined. Such performance measures, usually called signal‐to‐noise (S/N) ratios, are used to determine optimal settings of the controllable factors. Typically, a two‐step procedure is adopted in the Taguchi method. In the first step, the S/N ratio is maximized, whereas in the second step, using an adjustment factor that does not affect the S/N ratio, the mean response is adjusted to meet the target value, where appropriate. Experimental designs make use of orthogonal arrays to determine factor settings for obtaining data for subsequent analysis. The number of experimental runs is very modest in relation to the number of factors being investigated. WIREs Comp Stat 2011 3 472–480 DOI: 10.1002/wics.169 This article is categorized under: Statistical and Graphical Methods of Data Analysis > Robust Methods Data: Types and Structure > Time Series, Stochastic Processes, and Functional Data

Comparison of old and new measures of loss function. (Reprinted with permission from Ref 5. Copyright 2008 John Wiley & Sons)

[ Normal View | Magnified View ]

Loss function for a target‐is‐best characteristic. (Reprinted with permission from Ref 5. Copyright 2008 John Wiley & Sons)

[ Normal View | Magnified View ]

Effect of a parameter setting on the signal‐to‐noise ratio and the mean of the response variable. (Reprinted with permission from Ref 5. Copyright 2008 John Wiley & Sons)

[ Normal View | Magnified View ]

Adjustment parameter in Taguchi method. (Reprinted with permission from Ref 5. Copyright 2008 John Wiley & Sons)

[ Normal View | Magnified View ]

Robust design in Taguchi method. (Reprinted with permission from Ref 5. Copyright 2008 John Wiley & Sons)

[ Normal View | Magnified View ]

Related Articles

Statistical Methods

Browse by Topic

Data: Types and Structure > Time Series, Stochastic Processes, and Functional Data
Statistical and Graphical Methods of Data Analysis > Robust Methods

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts