Simultaneous Optimization of Multiple quality Characteristics to Robust Design using Desirability Function

로버스트 설계에서 기대함수를 이용한 다특성 동시 최적화 방안

  • Kwon, Yong-Man (Dept. of Computer Science and Statistics, Chosun University) ;
  • Park, Byung-Jun (Dept. of Computer Science and Statistics, Chosun University)
  • 권용만 (조선대학교 전산통계학과) ;
  • 박병전 (조선대학교 전산통계학과)
  • Published : 1999.06.01

Abstract

Robust design is an approach to reducing performance variation of quality characteristic values in quality engineering. Taguchi has an idea that mean and variation are handled simultaneously to reduce the expected loss in products and processes. Taguchi parameter design has a great deal of advantages but it also has some disadvantages. The various research efforts aimed at developing alternative methods. In the Taguchi parameter design, the product-array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. An alternative approach, which is called the combined-array approach, was suggested by Welch et. al. ( 1990) and studied by others. In these studies, only single quality characteristic was considered. In this paper we propose how to simultaneously optimize multiple quality characteristics using desirability function when we used the combined-array approach to assign control and noise factors. An example is illustrated to show the difference between the Taguchi's product-array approach and the combined-array approach.

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