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Taguchi Methods: Benefits, Impacts, Mathematics, Statistics and Applications

Teruo Mori, PhD
Teruo Mori, PhD
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Shih-Chung Tsai, PhD
Shih-Chung Tsai, PhD
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ASME Press
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Engineers in manufacturing industries face many challenges such as defects in production processes, warranty claims, troubleshooting issues, as well as constant changes in manufacturing conditions, which prevent productivity improvement. This chapter discusses the shortcomings of traditional product/process experimental optimization procedures compared to Taguchi Methods. Currently, the commonly used experimental optimization methods in manufacturing industries are one-factor-at-a-time or engineering judgment approaches. The one-factor-at-a-time method changes the setting of one factor to see its effect on the output while keeping the other factors constant. This approach is commonly used in academic and scientific research. Engineers use trends to identify optimal settings of...

7.1 Traditional Experimental Optimization Procedures
7.2 Input-Output Relationship Based on Input-Output Energy Transformation Approach
7.3 Improving the Effects of Individual Factors
7.4 Reproducibility of Traditional Experimental Optimization Methods
7.5 Traditional Experimental Optimization Methods Versus Taguchi Methods From the Viewpoint of Business Administrators
7.6 Taguchi Methods in the United States
7.7 Summary: Comparisons Between Traditional Experimental Optimization Methods and Taguchi Methods
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