Taguchi methods (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Taguchi methods" in English language version.

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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.

Woo, Seongwoo (2017-01-12). Reliability Design of Mechanical Systems: A Guide for Mechanical and Civil Engineers. Springer. pp. 86–89. ISBN 978-3-319-50829-0.
Statisticians have developed designs that enable experiments to use fewer replications (or experimental runs), enabling savings over Taguchi's proposed designs:
- 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. {{cite book}}: External link in |publisher= (help)

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.

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.

Statisticians have developed designs that enable experiments to use fewer replications (or experimental runs), enabling savings over Taguchi's proposed designs:
- 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. {{cite book}}: External link in |publisher= (help)

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, 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.