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      쌍대반응표면최적화의 방법론 및 응용 = A Literature Review

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      다국어 초록 (Multilingual Abstract)

      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 rece...

      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 (Reference)

      1 Yeniaya, O, "Using dual response surfaces to reduce variability in launch vehicle design : A case study" 91 : 407-412, 2006

      2 Shin, S, "Studies on a biobjective robust design optimization problem" 41 : 957-968, 2009

      3 Pignatiello, J, "Strategies for Robust Multiresponse Quality Engineering" 25 (25): 5-15, 1993

      4 Yang, T, "Solving a multiresponse simulation problem using a dual-response system and scatter search method" 13 (13): 356-369, 2005

      5 Derringer, G, "Simultaneous optimization of several response variables" 12 : 214-219, 1980

      6 Costa, N, "Simultaneous Optimization of Mean and Standard Deviation" 22 : 140-149, 2010

      7 Shin, S, "Robust design models for customerspecified bounds on process parameters" 15 : 2-18, 2006

      8 Myers, R. H, "Response Surface Methods for Dual Response Systems" 15 (15): 301-307, 1973

      9 Cho, B. R, "Quality improve ment by RSM Modeling for Robust Design" 650-655, 1996

      10 Jeyapaul, R, "Quality Management Research by Considering Multi-response Problems in the Taguchi Method : a Review" 26 : 1331-1337, 2005

      1 Yeniaya, O, "Using dual response surfaces to reduce variability in launch vehicle design : A case study" 91 : 407-412, 2006

      2 Shin, S, "Studies on a biobjective robust design optimization problem" 41 : 957-968, 2009

      3 Pignatiello, J, "Strategies for Robust Multiresponse Quality Engineering" 25 (25): 5-15, 1993

      4 Yang, T, "Solving a multiresponse simulation problem using a dual-response system and scatter search method" 13 (13): 356-369, 2005

      5 Derringer, G, "Simultaneous optimization of several response variables" 12 : 214-219, 1980

      6 Costa, N, "Simultaneous Optimization of Mean and Standard Deviation" 22 : 140-149, 2010

      7 Shin, S, "Robust design models for customerspecified bounds on process parameters" 15 : 2-18, 2006

      8 Myers, R. H, "Response Surface Methods for Dual Response Systems" 15 (15): 301-307, 1973

      9 Cho, B. R, "Quality improve ment by RSM Modeling for Robust Design" 650-655, 1996

      10 Jeyapaul, R, "Quality Management Research by Considering Multi-response Problems in the Taguchi Method : a Review" 26 : 1331-1337, 2005

      11 Tong, L, "Optimizing Dynamic Multiresponse Problems Using the Dual-Response-Surface Method" 14 (14): 115-125, 2002

      12 Chen, W, "Optimization of plastic injection molding process by dual response surface method with nonlinear programming" 27 (27): 951-966, 2010

      13 Kim, K, "Optimization of Multiple Responses Considering Both Location and Dispersion Effects" 169 : 133-145, 2006

      14 Kim, D, "Optimization of GMA welding process using the dual response approach" 41 (41): 4505-4515, 2003

      15 Jeong, I, "Optimal Weighting of Bias and Variance in Dual Response Surface Optimization" 37 (37): 236-247, 2005

      16 Hwang, C. L, "Multiple Objective Decision Making-Methods and Applications : A State of the Art Survey" Springer-Verlag 1979

      17 Borror, C. M, "Mean and variance modeling with qualitative responses : A case study" 11 (11): 141-148, 1998

      18 Koksoy, O, "Joint Optimization of Mean and Standard Deviation Using Response Surface Methods" 35 (35): 239-252, 2003

      19 Lee, D, "Interactive Weighting of Bias and Variance in Dual Response Surface Optimization" 39 (39): 5900-5906, 2012

      20 Shin, S, "Integrating a biobjective paradigm to tolerance optimization" 45 (45): 5509-5525, 2007

      21 Ding, R, "Dual-Response Surface Optimization : A Weighted MSE Approach" 16 (16): 377-385, 2004

      22 Coetzer, R. L. J, "Dual response surface optimization with hard-to-control variables for sustainable gasifier performance" 57 (57): 567-587, 2008

      23 Kim, K, "Dual Response Surface Optimization : A Fuzzy Modeling Approach" 30 (30): 1998

      24 Lin, D. and Tu, W., "Dual Response Surface Optimization" 27 (27): 34-39, 1995

      25 Wahdame, B., "Dual Response Surface Approach for the Analysis of a Fuel Cell Durability Test, IEEE Industrial Electronics, IECON 2006-32nd Annual Conference on" 4337-4342, 2006

      26 Copeland, K. A, "Dual Response Optimization via Direct Function Minimization" 28 (28): 331-336, 1996

      27 Kim, Y, "Development of Priority-Based Robust Design" 14 (14): 355-363, 2002

      28 Lee, D, "Determining the target value of ACICD to optimize the electrical characteristics of semiconductors using dual response surface optimization" John Wiley & Sons, Ltd. 29 (29): 377-386, 2013

      29 Vining, G. G, "Combining Taguchi and Response Surface Philosophies : A Dual Response Approach" 22 (22): 38-45, 1990

      30 Jeong, I, "Bayesian Analysis for Weighted Mean-Squared Error in Dual Response Surface Optimization" 26 (26): 417-430, 2010

      31 Ardakani, M. K, "An Overview of Optimization Formulations for Multiresponse Surface Problems" 29 : 3-16, 2012

      32 Lee, D, "An Interactive Method to Multiresponse Surface Optimization Based on Pairwise Comparisons" 44 (44): 13-26, 2012

      33 Luner, J. J, "Achieving Continuous Improvement with the Dual Response Approach : A Demonstration of the Roman Catapult" 6 (6): 691-705, 1994

      34 Tang, L. C, "A Unified Approach for Dual Response Surface Optimization" 34 (34): 437-447, 2002

      35 Lee, D, "A Review on Posterior and Interactive Solution Selection Methods to Multiresponse Surface Optimization" 18 (18): 279-301, 2011

      36 Murphy, T. E, "A Review of Robust Design Methods for Multiple Responses" 15 : 201-215, 2005

      37 Lee, D, "A Posterior Preference Articulation Approach to Multiresponse Surface Optimization" 210 (210): 301-309, 2011

      38 Lee, D, "A Posterior Preference Articulation Approach to Dual-Response Surface Optimization" 42 (42): 161-171, 2010

      39 Ko, Y, "A New Loss Function-Based Method for Multiresponse Optimization" 37 (37): 50-59, 2005

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      연월일 이력구분 이력상세 등재구분
      2021 평가예정 계속평가 신청대상 (등재유지)
      2016-01-01 평가 우수등재학술지 선정 (계속평가)
      2013-01-01 평가 등재학술지 유지 (기타) KCI등재
      2012-05-25 학술지명변경 외국어명 : Journal of the Korean Insitute of Industrial Engineers -> Journal of the Korean Institute of Industrial Engineers KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2008-01-01 평가 등재학술지 유지 (등재유지) KCI등재
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      2001-07-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      1999-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.65 0.65 0.66
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.56 0.47 1.026 0.14
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