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Design optimization using ANOVA

Author

Listed:
  • K. Hafeez
  • H. Rowlands
  • G. Kanji
  • S. Iqbal

Abstract

This paper describes the design optimization of a robot sensor used for locating 3-D objects employing the Taguchi method in a computer simulation scenario. The location information from the sensor is to be utilized to control the movements of an industrial robot in a 'pick-and-place' or assembly operation. The Taguchi method, which is based on the Analysis-of-Variance (ANOVA) approach, is utilized to improve the performance of the sensor over a wider operating range. A review of the Taguchi method is presented along with step-by-step implementation details to identify and optimize the design parameters of the sensor. The method allows us to gauge the impact of various interactions present in the sensor system exclusively and permits us to single out those factors that have a dominant influence on the overall performance of the sensor. The investigation suggests that the Taguchi method is a more structured and efficient approach for achieving a robust design compared with the classical full factorial design approach.

Suggested Citation

  • K. Hafeez & H. Rowlands & G. Kanji & S. Iqbal, 2002. "Design optimization using ANOVA," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(6), pages 895-906.
    • Handle: RePEc:taf:japsta:v:29:y:2002:i:6:p:895-906
    DOI: 10.1080/02664760220136203
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    References listed on IDEAS

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    1. T. N. Goh, 2001. "A pragmatic approach to experimental design in industry," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(3-4), pages 391-398.
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