대한산업공학회지 (Journal of Korean Institute of Industrial Engineers)

  • 제39권5호
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  • Pages.342-350
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  • 2013
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  • 1225-0988(pISSN)
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  • 2234-6457(eISSN)
대한산업공학회 (Korean Institute of Industrial Engineers)
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쌍대반응표면최적화의 방법론 및 응용 : A Literature Review

Methods and Applications of Dual Response Surface Optimization : A Literature Review

  • 이동희 (삼성전자 S.LSI 사업부 품질팀) ;
  • 정인준 (대구대학교 경영학과) ;
  • 김광재 (포항공과대학교 산업경영공학과)
  • Lee, Dong-Hee (S.LSI Business, Samsung Electronics) ;
  • Jeong, In-Jun (Department of Business Administration, Daegu University) ;
  • Kim, Kwang-Jae (Department of Industrial and Management Engineering, Pohang University of Science and Technology)
  • 투고 : 2013.07.27
  • 심사 : 2013.09.02
  • 발행 : 2013.10.15
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초록

Dual response surface optimization (DRSO), inspired by Taguchi's philosophy, attempts to optimize the process mean and variability by using response surface methodology. Researches on DRSO were extensively done in 1990's and have been matured recently. This paper reviews the existing DRSO methods from the decision making perspective. More specifically, this paper classifies the existing DRSO methods based on the optimization criterion and the timing of preference articulation. Also, some of case studies are reviewed. Extension to multiresponse optimization, triple response surface optimization, and application of data mining method are suggested as future research issues.

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참고문헌

  1. Ardakani, M. K. and Wulff, S. S. (2012), An Overview of Optimization Formulations for Multiresponse Surface Problems, Quality Reliability Engineering International, 29, 3-16.
  2. Borror, C. M. (1998), Mean and variance modeling with qualitative responses : A case study, Quality Engineering, 11(1), 141-148. https://doi.org/10.1080/08982119808919219
  3. Chen, W., Huang, C., and Hung, C. (2010), Optimization of plastic injection molding process by dual response surface method with nonlinear programming, Engineering Computations, 27(8), 951-966. https://doi.org/10.1108/02644401011082971
  4. Cho, B. R., Phillips, M. D., and Kapur, K. C. (1996), Quality improvement by RSM Modeling for Robust Design, Institute of Industrial Engineering, In : 5th Industrial Engineering Research Conference proceedings, Minneapolis, 650-655.
  5. Coetzer, R. L. J., Rossouw, R. F., and Lin, D. K. J. (2008), Dual response surface optimization with hard-to-control variables for sustainable gasifier performance, Journal of the Royal Statistical Society : Series C (Applied Statistics), 57(5), 567-587. https://doi.org/10.1111/j.1467-9876.2008.00631.x
  6. Copeland, K. A. and Nelson, P. R. (1996), Dual Response Optimization via Direct Function Minimization, Journal of Quality Technology, 28(3), 331-336. https://doi.org/10.1080/00224065.1996.11979683
  7. Costa, N. (2010), Simultaneous Optimization of Mean and Standard Deviation, Quality Engineering, 22, 140-149. https://doi.org/10.1080/08982110903394205
  8. Derringer, G. and Suich, R. (1980), Simultaneous optimization of several response variables, Journal of Quality Technology, 12, 214-219. https://doi.org/10.1080/00224065.1980.11980968
  9. Ding, R., Lin, D. K. J., and Wei, D. (2004), Dual-Response Surface Optimization : A Weighted MSE Approach, Quality Engineering, 16(3), 377-385. https://doi.org/10.1081/QEN-120027940
  10. Hwang, C. L., Masud, A. S. M., Paidy, S. R., and Yoon, K. (1979), Multiple Objective Decision Making-Methods and Applications : A State of the Art Survey, Springer-Verlag, Berlin.
  11. Jeong, I., Kim, K., and Chang, S. (2005), Optimal Weighting of Bias and Variance in Dual Response Surface Optimization, Journal of Quality Technology, 37(3), 236-247. https://doi.org/10.1080/00224065.2005.11980324
  12. Jeong, I., Kim, K., and Lin, D. (2010), Bayesian Analysis for Weighted Mean-Squared Error in Dual Response Surface Optimization, Quality and Reliability Engineering International, 26(5), 417-430.
  13. Jeyapaul, R., Shahabudeen, P., and Krishnaiah, K. (2005), Quality Management Research by Considering Multi-response Problems in the Taguchi Method : a Review, International Journal of Advanced Manufacturing Technology, 26, 1331-1337. https://doi.org/10.1007/s00170-004-2102-y
  14. Kim, D. and Rhee, S. (2003), Optimization of GMA welding process using the dual response approach, International Journal of Production Research, 41(18), 4505-4515. https://doi.org/10.1080/0020754031000/595800
  15. Kim, K. and Lin, D. (1998), Dual Response Surface Optimization : A Fuzzy Modeling Approach, Journal of Quality Technology, 30(1), 1-10. https://doi.org/10.1080/00224065.1998.11979814
  16. Kim, K. and Lin, D. (2006), Optimization of Multiple Responses Considering Both Location and Dispersion Effects, European Journal of Operational Research, 169, 133-145. https://doi.org/10.1016/j.ejor.2004.06.020
  17. Kim, Y. and Cho, B. (2002), Development of Priority-Based Robust Design, Quality Engineering, 14(3), 355-363. https://doi.org/10.1081/QEN-120001874
  18. Ko, Y., Kim, K., and Jun, C. (2005), A New Loss Function-Based Method for Multiresponse Optimization, Journal of Quality Technology, 37(1), 50-59. https://doi.org/10.1080/00224065.2005.11980300
  19. Koksoy, O. and Doganaksoy, N. (2003), Joint Optimization of Mean and Standard Deviation Using Response Surface Methods, Journal of Quality Technology, 35(3), 239-252. https://doi.org/10.1080/00224065.2003.11980218
  20. Lee, D. and Kim, K. (2011), A Review on Posterior and Interactive Solution Selection Methods to Multiresponse Surface Optimization, Journal of Quality, 18(4), 279-301.
  21. Lee, D. and Kim, K. (2012), Interactive Weighting of Bias and Variance in Dual Response Surface Optimization, Expert Systems with Applications, 39(5), 5900-5906. https://doi.org/10.1016/j.eswa.2011.11.114
  22. Lee, D. and Kim, K. (2013), Determining the target value of ACICD to optimize the electrical characteristics of semiconductors using dual response surface optimization, Applied Stochastic Models in Business and Industry, 29(4), 377-386. https://doi.org/10.1002/asmb.1973
  23. Lee, D., Jeong, I., and Kim, K. (2010), A Posterior Preference Articulation Approach to Dual-Response Surface Optimization, IIE Transaction, 42(2), 161-171.
  24. Lee, D., Kim, K., and Koksalan, M. (2011), A Posterior Preference Articulation Approach to Multiresponse Surface Optimization, European Journal of Operational Research, 210(2), 301-309. https://doi.org/10.1016/j.ejor.2010.09.032
  25. Lee, D., Kim, K., and Koksalan, M. (2012), An Interactive Method to Multiresponse Surface Optimization Based on Pairwise Comparisons, IIE Transactions, 44(1), 13-26. https://doi.org/10.1080/0740817X.2011.564604
  26. Lin, D. and Tu, W. (1995), Dual Response Surface Optimization, Journal of Quality Technology, 27(1), 34-39. https://doi.org/10.1080/00224065.1995.11979556
  27. Luner, J. J. (1994), Achieving Continuous Improvement with the Dual Response Approach : A Demonstration of the Roman Catapult, Quality Engineering, 6(4), 691-705. https://doi.org/10.1080/08982119408918759
  28. Murphy, T. E., Tsui, K.-L., and Allen, J. K. (2005), A Review of Robust Design Methods for Multiple Responses, Research in Engineering Design, 15, 201-215. https://doi.org/10.1007/s00163-004-0054-8
  29. Myers, R. H. and Carter, W. H. (1973), Response Surface Methods for Dual Response Systems, Technometrics, 15(2), 301-307. https://doi.org/10.1080/00401706.1973.10489044
  30. Pignatiello, J. (1993), Strategies for Robust Multiresponse Quality Engineering, IIE Transactions, 25(3), 5-15.
  31. Tang, L. C. and Xu, K. (2002), A Unified Approach for Dual Response Surface Optimization, Journal of Quality Technology, 34(3), 437-447. https://doi.org/10.1080/00224065.2002.11980175
  32. Shin, S. and Cho, B. R. (2006), Robust design models for customerspecified bounds on process parameters, Journal of Systems Science and Systems Engineering, 15, 2-18. https://doi.org/10.1007/s11518-006-0002-4
  33. Shin, S. and Cho, B. R. (2007), Integrating a biobjective paradigm to tolerance optimization, International Journal of Production Research, 45(23), 5509-5525. https://doi.org/10.1080/00207540701325181
  34. Shin, S. and Cho, B. R. (2009), Studies on a biobjective robust design optimization problem, IIE Transactions, 41, 957-968. https://doi.org/10.1080/07408170902789084
  35. Tong, L., Wang, C., Houng, C., and Chen, J. (2002), Optimizing Dynamic Multiresponse Problems Using the Dual-Response-Surface Method, Quality Engineering, 14(1), 115-125. https://doi.org/10.1081/QEN-100106891
  36. Vining, G. G. and Myers, R. H. (1990), Combining Taguchi and Response Surface Philosophies : A Dual Response Approach, Journal of Quality Technology, 22(1), 38-45. https://doi.org/10.1080/00224065.1990.11979204
  37. Wahdame, B., Candusso, D., Francois, X., Harel, F., Pera, M., Hissel, D., and Kauffmann, J. (2006), Dual Response Surface Approach for the Analysis of a Fuel Cell Durability Test, IEEE Industrial Electronics, IECON 2006-32nd Annual Conference on, 4337-4342.
  38. Yang, T., Kuo, Y., and Chou, P. (2005), Solving a multiresponse simulation problem using a dual-response system and scatter search method, Simulation Modeling Practice and Theory, 13(4), 356-369. https://doi.org/10.1016/j.simpat.2004.12.001
  39. Yeniaya, O., Unalb, R., and Lepsch, R. (2006), Using dual response surfaces to reduce variability in launch vehicle design : A case study, Reliability Engineering and System Safety, 91, 407-412. https://doi.org/10.1016/j.ress.2005.02.007

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