A literature review on RSM-based robust parameter design (RPD): Experimental design, estimation modeling, and optimization methods

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참고문헌 (143)

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16. Box, G. E. P., "Empirical model-building and response surfaces (Wiley Series in Probability and Statistics)" (1987), John Wiley & Sons
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28. Copeland, K. A. F., "Dual response optimization via direct function minimization", Journal of Quality Technology, 28(3), pp.331~336 (1996)[DOI]
29. Das, R. N., "Dual response surface methodology: Applicable always?", ProbStat Forum, 04, pp.98~103 (2011)
30. Wu, C. F. J., "Robust parameter design with feedback control", Technometrics, 48(3), pp.349~359 (2006)
31. Del Castillo, E., "A nonlinear programming solution to the dual response problem", Journal of Quality Technology, 25, pp.199~204 (1995)
32. Del Castillo, E., "Bayesian modeling and optimization of functional responses affected by noise factors", Journal of Quality Technology, 44(2), pp.117~135 (2012)[DOI]
33. Dellino, G., "Robust optimization in simulation: Taguchi and response surface methodology", International Journal of Production Economics, 125(1), pp.52~59 (2010)[DOI]
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36. Engel, J., "Modeling variation in industrial experiments", Journal of the Royal Statistical Society. Series C (Applied Statistics), 41(3), pp.579~593 (1992)
37. Engel, J., "A generalized linear modeling approach to robust design", Technometrics, 38(4), pp.365~373 (1996)[DOI]
38. Engel, J., "Taguchi parameter design by second-order response surfaces", Quality and Reliability Engineering International, 12(2), pp.95~100 (2007)
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40. Frey, D. D., "Validating robust-parameter-design methods", ASME 2004 Design Engineering Technical Conferences and Computers and Information in Engineering Conference, pp.459~471 (2004), American Society of Mechanical Engineers
41. A hierarchical Bayesian approach to robust parameter design, DTEW-KBI_0719, "Goegebeur, Y.", 1~22 (2007)
42. Goethals, P. L., "The development of a robust design methodology for time-oriented dynamic quality characteristics with a target profile", Quality and Reliability Engineering International, 27(4), pp.403~414 (2010)
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44. Grego, J. M., "Generalized linear models and process variation", Journal of Quality Technology, 25, pp.288~295 (1993)[DOI]
45. Hamada, M., "Generalized linear models for quality-improvement experiments", Journal of Quality Technology, 29, pp.292~304 (1997)[DOI]
46. Huber, P. J., "Robust Statistics" (1981), John Wiley & Sons
47. Jin, J., "Online automatic process control using observable noise factors for discrete-part manufacturing", IIE Transactions, 36, pp.899~911 (2004)[DOI]
48. Johnson, R. T., "Choice of second-order response surface designs for logistic and Poisson regression models", International Journal of Experimental Design and Process Optimization, 1(1), pp.2~23 (2009)[DOI]
49. Joseph, V. R., "Robust parameter design with feed-forward control", Technometrics, 45(4), pp.284~292 (2003)[DOI]
50. Kang, L., "Bayesian optimal single arrays for robust parameter design", Technometrics, 51(3), pp.250~261 (2009)[DOI]
51. Kasimbeyli, R., "A conic scalarization method in multi-objective optimization", Journal of Global Optimization, 56, pp.279~297 (2013)[DOI]
52. Khattree, R., "Robust parameter design: A response surface approach", Journal of Quality Technology, 28, pp.187~198 (1996)[DOI]
53. Khuri, A. I., "Response surface: design and analyses" (1987), CRC Press
54. Khuri, A. I., "Response surface methodology", Wiley Interdisciplinary Reviews: Computational Statistics, 2(2), pp.128~149 (2010)[DOI]
55. Kim, K. J., "Dual response surface optimization: A fuzzy modeling approach", Journal of Quality Technology, 30, pp.1~10 (1998)[DOI]
56. Kim, Y. J., "Economic considerations on parameter design", Quality and Reliability Engineering International, 16(6), pp.501~514 (2000)[DOI]
57. Kim, Y. J., "Development of priority-based robust design", Quality Engineering, 14, pp.355~363 (2002)[DOI]
58. Koksoy, O., "Multi-response robust design: Mean square error (MSE) criterion", Applied Mathematics and Computation, 175, pp.1716~1729 (2006)[DOI]
59. Koksoy, O., "A nonlinear programming solution to robust multi-response quality problem", Applied Mathematics and Computation, 196(2), pp.603~612 (2008)[DOI]
60. Koksoy, O., "Joint optimization of mean and standard deviation using response surface methods", Journal of Quality Technology, 35, pp.239~252 (2003)[DOI]
61. Koksoy, O., "Mean square error criteria to multi-response process optimization by a new genetic algorithm", Applied Mathematics and Computation, 175, pp.1657~1674 (2006)[DOI]
62. Kovach, J., "Development of a variance prioritized multi-response robust design framework for quality improvement", International Journal of Quality and Reliability Management, 26(4), pp.380~396 (2008)
63. Kovach, J., "Development of a variance prioritized multi-response robust design framework for quality improvement", International Journal of Quality and Reliability Management, 26(4), pp.380~396 (2008)
64. Le Tuan Ho, "Augmented Weighted Tchebycheff Modeling and Robust Design Optimization on a Drug Development Process", 대한산업공학회지, 39(5), pp.403~411 (2013), 대한산업공학회[DOI]
65. Lee, D. H., "A posterior preference articulation approach to dual-response-surface optimization", IIE Transactions, 42(2), pp.161~171 (2009)
66. Lee, M. S., "Expected desirability function: Consideration of both location and dispersion effects in desirability function approach", Quality Technology and Quantitative Management, 4(3), pp.365~377 (2007)[DOI]
67. Lee, S. B., "Development of robust design optimization using incomplete data", Computers & Industrial Engineering, 50, pp.345~356 (2006)[DOI]
68. Lee, S., "Development of a highly efficient and resistant robust design", International Journal of Production Research, 45(1), pp.157~167 (2007)[DOI]
69. Leon, R. V., "Performance measures independent of adjustment-An explanation and extension of Taguchi's signal-to-noise ratios", Technometrics, 29(3), pp.253~265 (1987)[DOI]
70. Lin, D. K. J., "Dual response surface optimization", Journal of Quality Technology, 27, pp.34~39 (1995)
71. Lindsey, J. K., "Fitting response surfaces with power transformations", Journal of the Royal Statistical Society. Series C (Applied Statistics), 21(3), pp.234~247 (1972)
72. Lizotte, D. J., "An experimental methodology for response surface optimization methods", Journal of Global Optimization, 52(4), pp.698~736 (2012)
73. Lucas, J. M., "How to achieve a robust process using response surface methodology", Journal of Quality Technology, 25, pp.248~260 (1994)
74. Luner, J. J., "Achieving continuous improvement with the dual response approach: A demonstration of the Roman catapult", Quality Engineering, 6(4), pp.691~705 (1994)
75. Marler, R. T., "Survey of multi-objective optimization methods for engineering", Structural and Multidisciplinary Optimization, 26, pp.369~395 (2004)[DOI]
76. Montgomery, D. C., "Using fractional factorial designs for robust process development", Quality Engineering, 3, pp.193~205 (1990)
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81. Myers, R. H., "Response surface methodology in quality improvement", Communications in Statistics-Theory and Methods, 20(2), pp.457~476 (1992)
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85. Myers, R. H., "Response surface alternatives to the Taguchi robust parameter design approach", The American Statistician, 46(2), pp.131~139 (1992)
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142. Zhou, X. J., "Ensemble of surrogate for dual response surface modeling in robust parameter design", Quality and Reliability Engineering International, 29(2), pp.173~197 (2013)[DOI]
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