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Taguchi Method

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Campus Monterrey

Design and Analysis of Experiments

Research

TAGUCHI METHOD

Fernando de Castro Palomino Siller – A01191233

Thursday, September 17th, 2015

Professor: Héctor Rincón

CONTENT

Introduction ……………………………….………………………………… 3

Why to use Taguchi Method ……………………………….……………. 3-4

Taguchi Method Strategy ……………………………….………………… 4

P-diagram ……………………………….………………………………….. 5

Quality Measurement ……………………………….……………………. 5-6

Signal To Noise (S/N) Ratios ……………………………….…………… 6-7

Static Versus Dynamic S/N Ratios……………………………….………. 7

Steps in Robust Parameter Design ……………………………….……. 7-8

Conclusions ……………………………….……………………………….. 8

Bibliography ……………………………….……………………………….. 9

Introduction

Taguchi methods are statistical methods developed by Dr. Genichi Taguchi to improve the quality of manufactured goods and greatly improve engineering productivity. Dr. Genichi Taguchi developed a method (also known as Robust Design) after the end of the Second World War and it has evolved over the last five decades. Many companies around the world have saved hundreds of millions of dollars by using this method in diverse industries like automobiles, xerography, telecommunications, electronics, software, etc. This method results in a much-reduced variance for the experiment with optimum settings of control parameters. Because Design of Experiments works extremely close with optimization of control parameters, you can achieve the best results with the Taguchi Method. Taguchi's uses functions that serve as objective functions for optimization, help in data analysis and prediction of optimum results. Even though it is the most powerful method available to reduce product cost, improve quality, and simultaneously reduce development interval, some professional statisticians have criticized the inefficiency of some of Taguchi's proposals.

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