대한기계학회논문집A (Transactions of the Korean Society of Mechanical Engineers A)

  • 제39권5호
  • /
  • Pages.535-541
  • /
  • 2015
  • /
  • 1226-4873(pISSN)
  • /
  • 2288-5226(eISSN)
대한기계학회 (The Korean Society of Mechanical Engineers)
권호 표지
DOI QR코드

DOI QR Code

강도조건을 고려한 벽걸이 모니터 브라켓 암의 다중목적 근사최적설계

Approximate Multi-Objective Optimization of A Wall-mounted Monitor Bracket Arm Considering Strength Design Conditions

  • 투고 : 2014.12.19
  • 심사 : 2015.03.19
  • 발행 : 2015.05.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 연구에서는 벽걸이 모니터 브라켓 암의 다중목적 근사최적설계를 수행하였다. 이를 위해 브라켓 암의 자유도를 고려하여 평면내의 회전 각도를 선정해 응력과 처짐량이 크게 발생하는 경우에 대한 최적화 문제를 정식화 하였다. 직교배열표와 반응표면법을 사용하여 평균 및 파라미터 분석을 통해 성능지수에 대한 설계변수 민감도를 확인하였으며, 중심합성계획법과 D-최적 계획법을 사용하여 목적함수와 제한조건함수에 대하여 반응표면 근사모델을 생성하고 $R^2$ 값을 통해 정확도를 평가하였다. 이를 비지배 분류 유전알고리즘에 적용하여 최적화를 수행하고 유한요소해석을 통해 검증하였다. 또한, 중심합성 계획법과 D-최적 계획법을 이용한 최적해를 비교 분석하였다.

In this study, an approximate multi-objective optimization of a wall-mounted monitor bracket arm was performed. The rotation angle of the bracket arm was determined considering the inplane degree of freedom. We then formulated an optimization problem on maximum stress and deflection. Analyses of mean and design parameters were conducted for sensitivity regarding performance with orthogonal array and response surface method (RSM). RSM models of objective and constraint functions were generated using central composite (CCD) and D-optimal design. The accuracy of approximate models was evaluated through $R^2$ value. The obtained optimal solutions by non-dominant sorting genetic algorithm (NSGA-II) were validated through the finite element analysis and we compared the obtained optimal solution by CCD and D-optimal design.

키워드

참고문헌

  1. Jung, S. and Kim, M., 2014, "Robust Rear Center-Hinge Bracket Optimization Based on Taguchi Method," Trans. Korean Soc. Auto. Eng., Vol. 22, No. 3, pp. 203-209. https://doi.org/10.7467/KSAE.2014.22.3.203
  2. Han, P.K. and Lee, J., 2009, A Response Surface Based Sequential Approximate Optimization Using Constrai-nt-Shifting Analogy, Journal of Mechanical Science and Technology, Vol. 23, pp. 1911-1923 https://doi.org/10.1007/s12206-009-0301-z
  3. Fowlkes, William Y., 1995, "Engineering Methods for Robust Product Design," Addison-Wesley, pp. 211-220.
  4. Park, S. H., 1995, "Modern Design of Experiments," Minyongsa, pp. 453-504.
  5. Triefenbach, F., 2008, "Design of Experiments: The D-optimal Approach and Its Implementation As a Computer Algorithm," Degree Thesis, Department of Computing Science, Umea University, Sweden.
  6. Hong, K. J., Jeon, K. K., Cho. Y. S., Choi, D. H. and Lee, S. J., 2000, "A Study on the Construction of Response Surface for Design Optimization," Trans. Korean Soc. Mech. Eng. A, Vol.24, No. 6, pp. 1408-1418. https://doi.org/10.22634/KSME-A.2000.24.6.1408
  7. Deb K., Pratap A., Agarwal S. and Meyarivan T., 2002, "A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II," IEEE Transactions on Evolutionary Computation, Vol. 6, No. 2, pp. 182-197. https://doi.org/10.1109/4235.996017
  8. HyperMesh User Guide, Version 11.0 2010, Altair Engineering Inc., Troy, MI.
  9. ABAQUS User's Manual Version 6.12, 2012, Dassault Systemes Simulia, Inc., Providence, RI.
  10. Lee, J. and Ahn, B., 2006, "DOE Based Robust Optimization Considering Tolerance Bands of Design Parameters," JSME Series C, Vol. 49, No. 4, pp. 1223-1231. https://doi.org/10.1299/jsmec.49.1223
  11. Nam, H., 2005, "Six Sigma Robust Design of Composite Hand for LCD Glass Transfer Robot," Trans. Korean Soc. Mech. Eng. A, Vol. 29, No. 3, pp. 455-451. https://doi.org/10.3795/KSME-A.2005.29.3.455
  12. SAS user's manual version 9.4, 2013. SAS Institute Cary, NC.