질의응답

참고문헌 (87)

1. Antony, J. (2000), Multi-Response Optimization in Industrial Experiments using Taguchi's Quality Loss Function and Principal Component Analysis, Quality and Reliability Engineering International, 16(1), 3-8. 

   상세보기

2. Ardakani, M. K. and Wulff, S. S. (2012), An Overview of Optimization Formulations for Multiresponse Surface Problems, Quality and Reliability Engineering International, 29(1), 3-16. 

3. Bisgaard, S. (1997), Design Experiments for Tolerancing Assembled Products, Technometrics, 39(2), 142-152. 

   상세보기

4. Bisgaard, S., Graves, S., and Shin, G. (2000), Tolerancing Mechanical Assemblies with CAD and DOE, Journal of Quality Technology, 32(3), 231-240. 

   상세보기

5. Box, G. (1988), Signal-to-Noise Ratios, Performance Criteria, and Transformations, with discussions, Technometrics, 30(1), 1-17. 

   상세보기

6. Box, G. and Jones, S. (1986), Discussion of "Testing in Industrial Experiments with Ordered Categorical Data" by V. N. Nair, Technometrics, 28(4), 295-301. 

   상세보기

7. Box, G. and Jones, S. (1992), Split-Plot Designs for Robust Product Experimentation, Journal of Applied Statistics, 19(1), 3-26. 

   상세보기

8. Byun, J. H. and Kim, K. J. (1998), A Desirability Function Approach to the Robust Design for Multiple Quality Characteristics, Journal of the Korean Institute of Industrial Engineers, 24(2), 287-296. 

   원문보기 상세보기

9. Cho, B. R., Kim, Y. J., Kimbler, D. L., and Phillips, M. D. (2000), An Integrated Joint Optimization Procedure for Robust and Tolerance Design, International Journal of Production Research, 38(10), 2309-2325. 

   상세보기

10. Del Castillo, E. and Montgomery, D. C. (1993), A Nonlinear Programming Solution to the Dual Response Problem, Journal of Quality Technology, 25(3), 199-204. 

    상세보기

11. Deng, J. L. (1982), Control Problems of Grey Systems, Systems and Control Letters, 1(5), 288-294. 

    상세보기

12. D'Errico, J. R. and Zaino, Jr., N. A. (1988), Statistical Tolerancing Using Modification of Taguchi's Method, Technometrics, 30(4), 397-405. 

    상세보기

13. Derringer, G. and Suich, R. (1980), Simultaneous Optimization of Several Response Variables, Journal of Quality Technology, 12(4), 214-219. 

    상세보기

14. Faraway, J. J. (1997), Regression Analysis for a Functional Response, Technometrics, 39(3), 254-261. 

    상세보기

15. Fogliatto, F. S. (2008), Multiresponse Optimization of Products with Functional Quality Characteristics, Quality and Reliability Engineering International, 24(8), 927-939. 

    상세보기

16. Gauri, S. K. and Pal, S. (2010), Comparison of Performances of Five Prospective Approaches for the Multi-Response Optimization, International Journal of Advanced Manufacturing Technology, 48(9-12), 1205-1220. 

    상세보기

17. Goethals, P. L. and Cho, B. R. (2011), The Development of a Robust Design Methodology for Time-oriented Dynamic Quality Characteristics with a Target Profile, Quality and Reliability Engineering International, 27(4), 403-414. 

    상세보기

18. Govaerts, B. and Noel, J. (2005), Analysing the Results of a Designed Experiment When the Response is a Curve : Methodology and Application in Metal Injection Moulding, Quality and Reliability Engineering International, 21(5), 509-520. 

    상세보기

19. Hamada, M. (1992), An Explanation and Criticism of Minute Accumulating Analysis, Journal of Quality Technology, 24(2), 70-77. 

20. Hamada, M. and Nelder, J. A. (1997), Generalized Linear Models for Quality Improvement Experiments, Journal of Quality Technology, 29(3), 292-304. 

    상세보기

21. Hamada, M. and Wu, C. F. J. (1990), A Critical Look at Accumulation Analysis and Related Methods, with discussions, Technometrics, 32(2), 119-130. 

    상세보기

22. Hirotsu, C. (1990), Discussion of "A Critical Look at Accumulation Analysis and Related Methods" by M. Hamada and C. F. J. Wu, Technometrics, 32(2), 133-136. 

23. Jeang, A. (1999), Optimal Tolerance Design by Response Surface Methodology, International Journal of Production Research, 37(14), 3275- 3288. 

    상세보기

24. Jeng, Y. C. and Guo, S. M. (1996), Quality Improvement for RC06 Chip Resistor, Quality and Reliability Engineering International, 12(6), 439-445. 

    상세보기

25. 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(11-12), 1331-1337. 

    상세보기

26. Joseph, V. R. and Wu, C. F. J. (2002), Robust Parameter Design of Multiple Target Systems, Technometrics, 44(4), 338-346. 

    상세보기

27. Jung, J. R. and Yum, B. J. (2011), Uniformity and Signal-to-noise Ratio for Static and Dynamic Parameter Designs of Deposition Processes, International Journal of Advanced Manufacturing Technology, 54(5-8), 619-628. 

    상세보기

28. Kackar, R. N. (1985), Off-Line Quality Control, Parameter Design, and the Taguchi Method, with discussions, Journal of Quality Technology, 17(4), 176-188. 

    상세보기

29. Kim, S. J. (2005), An Application of Fuzzy Logic with Desirability Functions to Multi-response Optimization in the Taguchi Method, International Journal of Fuzzy Logic and Intelligent Systems, 5(3), 183-188. 

    원문보기 상세보기

30. Kim, S. J. (2013), A Review on the Taguchi Method and Its Alternatives for Dynamic Robust Design, Journal of the Korean Institute of Industrial Engineers, 39(5), 351-360. 

    원문보기 상세보기

31. Kim, Y. J. (2002), Response Surface Approach to Integrated Optimization Modeling for Parameter and Tolerance Design, Journal of the Korean Society for Quality Management, 30(4), 58-67. 

    상세보기

32. Kuhn, A. M., Carter, W. H., and Myers, R. H. (2000), Incorporating Noise Factors into Experiments with Censored Data, Technometrics, 42(4), 376-383. 

    상세보기

33. Lee, Y. and Nelder, J. A. (2003), Robust Design via Generalized Linear Models, Journal of Quality Technology, 35(1), 2-12. 

    상세보기

34. Lee, P. H. and Yum, B. J. (2003), Multi-Characteristics Parameter Design : A Desirability Function Approach Based on Process Capability Indices, International Journal of Reliability, Quality, and Safety Engineering, 10(4), 445-461. 

    상세보기

35. Leon, R. V., Shoemaker, A. C., and Kacker, R. N. (1987), Performance Measures Independent of Adjustment: An Explanation and Extension of Taguchi's Signal-to-Noise Ratios, with discussions, Technometrics, 29(3), 253-265. 

    상세보기

36. Lesperance, M. L. and Park, S. M. (2003), GLMs for the Analysis of Robust Designs with Dynamic Characteristics, Journal of Quality Technology, 35(3), 253-263. 

    상세보기

37. Liao, H. C. (2006), Multi-Response Optimization Using Weighted Principal Component, International Journal of Advanced Manufacturing Technology, 27(7-8), 720-725. 

    상세보기

38. Lin, D. and Tu, W. (1995), Dual Response Surface Optimization, Journal of Quality Technology, 27(1), 34-39. 

    상세보기

39. Lin, J. L. and Lin, C. L. (2002), The Use of the Orthogonal Array with Grey Relational Analysis to Optimize the Electrical Discharge Machining Process with Multiple Performance Characteristics, International Journal of Machine Tools and Manufacture, 42(2), 237-244. 

    상세보기

40. Lin, J. L. and Tarng Y. S. (1998), Optimization of the Multi-response Process by the Taguchi Method with Grey Relational Analysis, Journal of Grey System, 10(4), 355-370. 

41. Lin, J. L., Wang, K. S., Yan, B. H., and Tarng, Y. S. (2000), Optimization of the Electrical Discharge Machining Process Based on the Taguchi Method with Fuzzy Logics, Journal of Material Processing Technology, 102(1-3), 48-55. 

    상세보기

42. Logothetis, N. (1990), Box-Cox Transformations and the Taguchi Method, Applied Statistics, 39(1), 31-48. 

    상세보기

43. Lucas, J. M. (1994), How to Achieve a Robust Process Using Response Surface Methodology, Journal of Quality Technology, 26(4), 248-260. 

    상세보기

44. 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(4), 201-215. 

    상세보기

45. Myers, R. H., Khuri, A. I. and Vining, G. (1992), Response Surface Alternatives to the Taguchi Robust Parameter Design Approach, The American Statistician, 46(2), 131-139. 

    상세보기

46. Myers, W. R., Brenneman, W. A., and Myers, R. H. (2005), A Dual-Response Approach to Robust Parameter Design for a Generalized Linear Model, Journal of Quality Technology, 37(2), 130-138. 

    상세보기

47. Nair, V. N. (1986), Testing in Industrial Experiments with Ordered Categorical Data, Technometrics, 28(4), 283-291. 

    상세보기

48. Nair, V. N. (Ed.) (1992), Taguchi's Parameter Design : A Panel Discussion, Technometrics, 34(2), 127-161. 

    상세보기

49. Nair, V. N. and Pregibon, D. (1986), A Data Analysis Strategy for Quality Engineering Experiments, AT&T Technical Journal, 65(3), 73-84. 

    상세보기

50. Nair, V. N., Taam, W. and Ye, K. Q. (2002), Analysis of Functional Responses from Robust Design Studies, Journal of Quality Technology, 34(4), 355-370. 

    상세보기

51. Nelder, J. A. and Lee, Y. (1991), Generalized Linear Models for the Analysis of Taguchi-type Experiments, Applied Stochastic Models and Data Analysis, 7(1), 107-120. 

    상세보기

52. Opricovic, S. and Tzeng, G. H. (2004), Compromise Solution by MCDM Methods : A Comparative Analysis of VIKOR and TOPSIS, European Journal of Operational Research, 156(2), 445-455. 

    상세보기

53. Pal, S. and Gauri, S. K. (2010), Assessing Effectiveness of the Various Performance Metrics for Multi-response Optimization Using Multiple Regression, Computers and Industrial Engineering, 59(4), 976-985. 

    상세보기

54. Phadke, M. S. (1989), Quality Engineering Using Robust Design, Prentice Hall, Englewood Cliffs, NJ. 

55. Pukelsheim, F. (2006), Optimal Design of Experiments, Society for Industrial and Applied Mathematics, Philadelphia, PA. 

56. Robinson, T. J., Borror, C., and Myers, R. H. (2004), Robust Parameter Design : A Review, Quality and Reliability Engineering International, 20(1), 81-101. 

    상세보기

57. Seo, H. S. and Kwak, B. M. (2002), Efficient Statistical Tolerance Analysis for General Distributions Using Three-point Information, International Journal of Production Research, 40(4), 931-944. 

    상세보기

58. Seo, S. K. and Choi, J. D. (1994), Robust Parameter Design for Multiple Performance Characteristics, Journal of the Korean Society for Quality Management, 22(3), 34-53. 

59. Shiau, G. H. (1990), A Study of the Sintering Properties of Iron Ores using the Taguchi's Parameter Design. Journal of Chinese Statistical Association, 28(2), 253-275. 

60. Shoemaker, A. C., Tsui, K. L., and Wu, C. F. J. (1991), Economical Experimentation Methods for Robust Design, Technometrics, 33(4), 415-427. 

    상세보기

61. Singh, P. K., Jain, P. K., and Jain, S. C. (2009a), Important Issues in Tolerance Design of Mechanical Assemblies. Part 1 : Tolerance Analysis, Proceedings of the Institution of Mechanical Engineers, Journal of Engineering Manufacture-Part B, 223(10), 1225-1247. 

    상세보기

62. Singh, P. K., Jain, P. K. and Jain, S. C. (2009b), Important Issues in Tolerance Design of Mechanical Assemblies. Part 2 : Tolerance Synthesis, Proceedings of the Institution of Mechanical Engineers, Journal of Engineering Manufacture-Part B, 223(10), 1249-1287. 

    상세보기

63. Soh, W. and Yum, B. J. (2012), A Comparison of Parameter Design Methods for Multiple Performance Characteristics, Journal of the Korean Institute of Industrial Engineers, 38(3), 198-207. 

    원문보기 상세보기

64. Su, C. T. and Tong, L. I. (1997), Multi-response Robust Design by Principal Component Analysis, Total Quality Management, 8(6), 409-416. 

    상세보기

65. Taguchi, G. (1978), Performance Analysis Design, International Journal of Production Research, 16(6), 521-530. 

    상세보기

66. Taguchi, G. (1986), Introduction to Quality Engineering, Asian Productivity Organization, Tokyo. 

67. Taguchi, G. (1987), System of Experimental Design, Vols. 1 and 2, UNIPUB/Kraus International Publications, White Plains, NY. 

68. Taguchi, G. (1988a), Quality Engineering in Research and Development, Quality Engineering Series, Volume 1, JSA, Tokyo (Korean edition published by KSA, 1991). 

69. Taguchi, G. (1988b), Design of Experiments for Quality Design, Quality Engineering Series, Volume 4, JSA, Tokyo (Korean edition published by KSA, 1991). 

70. Taguchi, G. (1988c), Quality Engineering Case Studies from Japan, Quality Engineering Series, Volume 5, JSA, Tokyo (Korean edition published by KSA, 1991). 

71. Taguchi, G. (1990a), Quality Engineering Case Studies from the United States and Europe, Quality Engineering Series, Volume 6, JSA, Tokyo (Korean edition published by KSA, 1991). 

72. Taguchi, G. (1990b), Quality Engineering Case Studies in Measurement, Quality Engineering Series, Volume 7, JSA, Tokyo (Korean edition published by KSA, 1991). 

73. Taguchi, G., Chowdhury, S., and Wu, Y. (2005), Taguchi's Quality Engineering Handbook, Wiley, NJ. 

74. Taguchi, G. and Konishi, S. (1959), Experimental Assignment Methods Using Orthogonal Tables (in Japanese), JUSE Press, Tokyo. 

75. Tai, C. Y., Chen, T. S., and Wu, M. C. (1992), An Enhanced Taguchi Method for Optimizing SMT Processes, Journal of Electronics Manufacturing, 2(3), 91-100. 

    

76. Tarng, Y. S., Juang, S. C. and Chang, C. H. (2002), The Use of Grey-Based Taguchi Methods to Determine Submerged are Welding Process Parameters in Hardfacing, Journal of Material Processing Technology, 128(1-3), 1-6. 

    상세보기

77. Tong, L. I. and Su, C. T. (1997), Optimizing Multi-response Problems in the Taguchi Method by Fuzzy Multiple Attribute Decision Making, Quality and Reliability Engineering International, 13(1), 25-34. 

    상세보기

78. Tong, L. I., Chen, C. C., and Wang, C. H. (2007), Optimization of Multiresponse Processes Using the VIKOR Method, International Journal of Advanced Manufacturing Technology, 31(11-12), 1049-1057. 

    상세보기

79. Tribus, M. and Szonyi, G. (1989), An Alternative View of the Taguchi Approach, Quality Progress, 22(5), 46-52. 

80. 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. 

    상세보기

81. Welch, W. J., Yu, T. K., Kang, S. M., and Sacks, J. (1990), Computer Experiments for Quality Control by Parameter Design, Journal of Quality Technology, 22(1), 15-22. 

    상세보기

82. Wu, C. F. J. and Chen, Y. Y. (1992), A Graph-Aided Method for Planning Two-Level Experiments When Certain Interactions are Important, Technometrics, 34(2), 162-175. 

    상세보기

83. Wu, C. F. J. and Hamada, M. S. (2009), Experiments : Planning, Analysis, and Optimization, 2nd Ed., Wiley, Hoboken, NJ. 

84. Wu, F. C. and Yeh, C. H. (2006), A Comparative Study on Optimization Methods for Experiments with Ordered Categorical Data, Computers and Industrial Engineering, 50(3), 220-232. 

    상세보기

85. Yadav, O. P., Bhamare, S. S., and Rathore, A. (2010), Reliability-Based Robust Design Optimization : A Multi-Objective Framework Using Hybrid Quality Loss Function, Quality and Reliability Engineering International, 26(1), 27-41. 

    상세보기

86. Yum, B. J., Ko, S. W., and Kim, S. J. (1990), The Taguchi Method for Product and Process Designs, Korean Management Science Review, 7(2), 3-21. 

87. Yum, B. J., Lee, B. Y., Ko, S. W., and Kim, J. H. (1991), Principles for Constructing Taguchi Experimental Designs, The Korean Journal of Applied Statistics, 4(1), 47-63. 

저자의 다른 논문 :

염봉진 (10) 서순근 (51) 변재현 (59) 이승훈 (14)