대한산업공학회지 (Journal of Korean Institute of Industrial Engineers)

  • 제39권5호
  • /
  • Pages.374-382
  • /
  • 2013
  • /
  • 1225-0988(pISSN)
  • /
  • 2234-6457(eISSN)
대한산업공학회 (Korean Institute of Industrial Engineers)
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종이 헬리콥터 실험을 통한 강건설계의 이해

Understanding Robust Design with Paper Helicopter Experiment

  • 변재현 (경상대학교 산업시스템공학부) ;
  • 김용태 (경상대학교 산업시스템공학부) ;
  • 이민지 (경상대학교 산업시스템공학부)
  • Byun, Jai-Hyun (Department of Industrial and Systems Engineering and Engineering Research Institute Gyeongsang National University) ;
  • Kim, Yong Tae (Department of Industrial and Systems Engineering and Engineering Research Institute Gyeongsang National University) ;
  • Lee, Min Ji (Department of Industrial and Systems Engineering and Engineering Research Institute Gyeongsang National University)
  • 투고 : 2013.07.24
  • 심사 : 2013.09.10
  • 발행 : 2013.10.15
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초록

Robust design method developed by Genichi Taguchi has been very popular since the 1980s and there have been many academic and applied research works on this topic. However, college students and engineers in companies have had difficulty in understanding the method. This paper presents a procedure to implement the robust design method by an easy-to-execute paper helicopter experiment. A crossed array was adopted, which consists of a resolution IV fractional factorial design with 6 control factors and a factorial design with 3 noise factors. Three performance measures were analyzed; signal-to-noise ratio, mean, and standard deviation of the falling time of the paper helicopter that is to be maximized. Control-noise interaction plots are also given to evaluate the degree of the sensitivity of each level of the control factors to the noise factors. The procedure presented in this paper can be helpful to those who want to have basic knowledge in the robust design method.

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참고문헌

  1. Box, G. E. P. (1988), Signal-to-Noise Ratios, Performance Criteria, and Transformations (with discussion), Technometrics, 30(1), 17-40.
  2. Box, G. E. P. and Liu, P. Y. T. (1999), Statistics as a Catalyst to Learning by Scientific Method Part I-An Example, Journal of Quality Technology, 31(1), 1-15. https://doi.org/10.1080/00224065.1999.11979889
  3. Myers, R. H. and Montgomery, D. C. (2002), Response Surface Methodology : Process and Product Optimization Using Designed Experiments, 2nd Edition, Wiley, New York.
  4. Nair, V. N. (ed.) (1992), Taguchi's Parameter Design : A Panel Discussion, Technometrics, 34(2), 127-161. https://doi.org/10.1080/00401706.1992.10484904
  5. Phadke, M. S. (1989), Quality Engineering Using Robust Design, Prentice-Hall, London.
  6. Ross, P. J. (1988), Taguchi Techniques for Quality Engineering, McGraw-Hill, New York.
  7. Shoemaker, A. C., Tsui, K.-L., and Wu, C. F. J. (1991), Economic Experimentation Methods for Robust Design, Technometrics, 33(4), 415-427. https://doi.org/10.1080/00401706.1991.10484870
  8. Welch, W. J., Yu, T. K., Kang, S. M., and Sacks, J. (1990), Computer Experiments for Quality Control by Parameter Design, Journal of Quality Technology, 22(1), 15-22. https://doi.org/10.1080/00224065.1990.11979201
  9. Yum, B.-J., Kim, S.-J., Seo, S.-K., Byun, J.-H., and Lee, S. -H. (2013), The Taguchi Robust Design Method : Current Status and Future Directions, Journal of the Korean Institute of Industrial Engineers, 39(5), 325-341. https://doi.org/10.7232/JKIIE.2013.39.5.325