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Tolerance Optimization of Lower Arm Used in Automobile Parts Considering Six Sigma Constraints

식스시그마 제약조건을 고려한 로워암의 공차 최적설계

  • Received : 2011.05.20
  • Accepted : 2011.07.11
  • Published : 2011.10.01

Abstract

In the current design process for the lower arm used in automobile parts, an optimal solution of its various design variables should be found through exploration of the design space approximated using the response surface model formulated with a first- or second-order polynomial equation. In this study, a multi-level computational DOE (design of experiment) was carried out to explore the design space showing nonlinear behavior, in terms of factors such as the total weight and applied stress of the lower arm, where a fractional-factorial orthogonal array based on the artificial neural network model was introduced. In addition, the tolerance robustness of the optimal solution was estimated using a tolerance optimization with six sigma constraints, taking into account the tolerances occurring in the design variables.

자동차 로워암과 같이 다양한 형상설계변수를 갖는 부품모듈의 최근 설계경향은 설계자가 관심을 갖는 설계영역을 선형 및 2 차 다항식으로 근사화시키는 반응표면모델로 탐색하고, 다음 단계로서 최적설계를 수행하는 것이다. 본 연구에서는 로워암의 설계변수 변화에 따른 작용응력과 중량의 비선형적 변화뿐만 아니라 이의 예측에 적합한 신경망모델로 직교성과 균형성을 모두 만족시키는 다수준 전산실험계획법으로 설계영역을 탐색하였다. 구축된 신경망모델에 형상 설계변수의 공차도 같이 고려할 수 있는 식스시그마 제약조건을 적용하여 로워암의 공차 최적설계를 수행하고, 최적해의 공차 강건성을 확보하였다.

Keywords

References

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