Comparison Design of Experiment (DOE): Taguchi Method and Full Factorial Design in Surface Roughness

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Statistical quality improvement techniques such as design of experiments (DOE) and Taguchi methods form an essential part of the search for improved product performance. This paper applies both the Taguchi and full factorial design techniques to highlight the application and to compare the effectiveness of the Taguchi and full factorial design processes as applied on surface roughness. Besides that, to determine the optimal parameter setting for each factor in surface roughness. For this study, we used two different probes of Mahr Surf XR20 which was MFW 250 tracing arm 6851804 (25μm) and tracing arm 6851806 (50μm). The main effect and interaction plot had been analyzed by using MINITAB (software). The experiment result showed that full factorial design performs better than Taguchi method.

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275-279

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October 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] M. Tanco, E. Viles and L. Pozueta, Comparing Different Approaches for Design of Experiments (DOE). Adv. In Electrical Engineering and Computational Science, Chapter 52, 2009, pp.611-621.

DOI: 10.1007/978-90-481-2311-7_52

Google Scholar

[2] A.J. Thomas and J. Antony, A Comparative Analysis of the Taguchi and Shainin DOE Techniques in an Aerospace Environment. International Journal of Productivity and Performance Management, Vol. 54, No. 8, 2005, pp.658-678.

DOI: 10.1108/17410400510627516

Google Scholar

[3] G. Taguchi, Introduction to Quality Engineering. White Plains, NY: UNIPUB/Kraus International, (1986).

Google Scholar

[4] R. H. Myers and D. C. Montgomery: Response Surface Methodology, A Wiley-Interscience Publication. (2002).

Google Scholar

[5] S. H. Park, Design of Experiments, Minyoungsa. (2002).

Google Scholar

[6] G. Taguchi, System of Experimental Design, 1/2, ASI, Dearborn, MI, 1, 2. (1987).

Google Scholar

[7] J. Antony, M. Kaye and A. Frangou, A Strategic Methodology to the Use Of Advanced Statistical Quality Improvement Techniques, The TQM Magazine, Vol. 10 No. 3, 1998, pp.169-76.

DOI: 10.1108/09544789810214765

Google Scholar

[8] A. Srinivas and Y. D. Venkatesh, Application Of Taguchi Method For Optimization Of Process Parameters In Improving The Surface Roughness Of Lathe Facing Operation, Vol. 1, Issue 3, 2012, pp.13-19.

Google Scholar

[9] Information on http: /www. minitab. co. kr.

Google Scholar