Statistical methods to improve the quality of manufactured goods
Taguchi methods (Japanese: タグチメソッド) are statistical methods, sometimes called robust design methods, developed by Genichi Taguchi to improve the quality of manufactured goods, and more recently also applied to engineering,[1] biotechnology,[2][3] marketing and advertising.[4] Professional statisticians have welcomed the goals and improvements brought about by Taguchi methods,[editorializing] particularly by Taguchi's development of designs for studying variation, but have criticized the inefficiency of some of Taguchi's proposals.[5][citation needed]
Taguchi's work includes three principal contributions to statistics:
A specific loss function
The philosophy of off-line quality control; and
Innovations in the design of experiments.
^Rosa, Jorge Luiz; Robin, Alain; Silva, M. B.; Baldan, Carlos Alberto; Peres, Mauro Pedro (2009). "Electrodeposition of copper on titanium wires: Taguchi experimental design approach". Journal of Materials Processing Technology. 209 (3): 1181–1188. doi:10.1016/j.jmatprotec.2008.03.021.
^Rao, Ravella Sreenivas; C. Ganesh Kumar; R. Shetty Prakasham; Phil J. Hobbs (March 2008). "The Taguchi methodology as a statistical tool for biotechnological applications: A critical appraisal". Biotechnology Journal. 3 (4): 510–523. doi:10.1002/biot.200700201. PMID 18320563. S2CID 26543702. Archived from the original on 2013-01-05. Retrieved 2009-04-01.
^Rao, R. Sreenivas; R.S. Prakasham; K. Krishna Prasad; S. Rajesham; P.N. Sarma; L. Venkateswar Rao (April 2004). "Xylitol production by Candida sp.: parameter optimization using Taguchi approach". Process Biochemistry. 39 (8): 951–956. doi:10.1016/S0032-9592(03)00207-3.
^Selden, Paul H. (1997). Sales Process Engineering: A Personal Workshop. Milwaukee, Wisconsin: ASQ Quality Press. p. 237. ISBN 0-87389-418-9.
^
Professional statisticians have welcomed Taguchi's concerns and emphasis on understanding variation (and not just the mean):
Logothetis, N.; Wynn, H. P. (1989). Quality Through Design: Experimental Design, Off-line Quality Control, and Taguchi's Contributions. Oxford University Press, Oxford Science Publications. pp. 464+xi. ISBN 0-19-851993-1.
Wu, C. F. Jeff; Hamada, Michael (2002). Experiments: Planning, Analysis, and Parameter Design Optimization. Wiley.
Box, G. E. P. and Draper, Norman. 2007. Response Surfaces, Mixtures, and Ridge Analyses, Second Edition [of Empirical Model-Building and Response Surfaces, 1987], Wiley.
Atkinson, A. C.; Donev, A. N.; Tobias, R. D. (2007). Optimum Experimental Designs, with SAS. Oxford University Press. pp. 511+xvi. ISBN 978-0-19-929660-6.
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