A review of data mining applications for quality improvement in manufacturing industry

Expert Systems with Applications

Volumn 38, Issue 10, 2011, Pages 13448-13467

  Köksal, Gülser ^a   Batmaz, Inci ^a   Testik, Murat Caner ^b  

^a MIDDLE EAST TECHNICAL UNIVERSITY   (Turkey)

^b HACETTEPE UNIVERSITY   (Turkey)

Author keywords

Classification; Data mining; Data mining software; Design for six sigma; Knowledge discovery in databases; Manufacturing; Parameter optimisation; Prediction; Quality description; Quality improvement; Six sigma

Indexed keywords

CLASSIFICATION; DATA MINING SOFTWARE; DESIGN FOR SIX SIGMA; KNOWLEDGE DISCOVERY IN DATABASES; MANUFACTURING; PARAMETER OPTIMISATION; PREDICTION; QUALITY DESCRIPTION; QUALITY IMPROVEMENT; SIX SIGMA;

DATA HANDLING; DATA MINING; INDUSTRY; OPTIMIZATION; WORK SIMPLIFICATION;

QUALITY CONTROL;

EID: 79957992809     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.04.063     Document Type: Review

References (164)

1. S. Achiche, L. Baron, M. Balazinski, and M. Benaoudia Online prediction of pulp brightness using fuzzy logic models Engineering Applications of Artificial Intelligence 20 1 2007 25 36 (Pubitemid 44780741)
2. O.G. Ali, and Y. Chen Design quality and robustness with neural networks IEEE Transactions on Neural Networks 10 6 1999 1518 1527 (Pubitemid 30536573)
3. D.H. Baek, I.J. Jeong, and C.H. Han Application of data mining for improving yield in water fabrication system O. Gervasi, Computational science and its applications - ICCSA 2005, 9-12 May 2005 Singapore Vol. 3483 2005 Springer-Verlag Berlin 222 231 (Pubitemid 41313421)
4. J.G. Baek, C.O. Kim, and S.S. Kim Online learning of the cause-and-effect knowledge of a manufacturing process International Journal of Production Research 40 14 2002 3275 3291
5. I. Batmaz Data mining applications on manufacturing data: A casting quality improvement case H.O. Ayhan, I. Batmaz, Recent advances in statistics 2007 TUIK Ankara, Turkey 197 206
6. E. Bertino, B. Catania, and E. Caglio Applying data mining techniques to wafer manufacturing Principles of Data Mining and Knowledge Discovery 1704 1999 41 50
7. J.E. Brady, and T.T. Allen Six sigma literature: A review and agenda for future research Quality and Reliability Engineering International 22 2006 335 367 (Pubitemid 43666594)
8. D. Braha, and A. Shmilovici Data mining for improving a cleaning process in the semiconductor industry IEEE Transactions on Semiconductor Manufacturing 15 1 2002 91 101 (Pubitemid 34278389)
9. D. Braha Data mining for design and manufacturing: Methods and applications 2001 Kluwer Academic Publishers Dordrecht
10. E. Brinksmeier, H.K. Tönshoff, C. Czenkusch, and C. Heinzel Modeling and optimization of grinding processes Journal of Intelligent Manufacturing 9 4 1998 303 314
11. K. Brudzewski, A. Kesik, K. Kolodziejczyk, U. Zborowska, and J. Ulaczyk Gasoline quality prediction using gas chromatography and FTIR spectroscopy: An artificial intelligence approach Fuel 85 4 2006 553 558
12. D.S. Chang, and S.T. Jiang Assessing quality performance based on the on-line sensor measurements using neural networks Computers and Industrial Engineering 42 2-4 2002 417 424 (Pubitemid 34410768)
13. P.C. Chang, C.H. Liu, C.Y. Fan, and H.C. Chang Data clustering and fuzzy neural network for sales forecasting in printed circuit board industry Proceedings of the 2007 IEEE symposium on computational intelligence and data mining (CIDM 2007) 2007 IEEE Honolulu, HI 107 113
14. C.R. Chen, and H.S. Ramaswamy Modeling and optimization of variable retort temperature (VRT) thermal processing using coupled neural networks and genetic algorithms Journal of Food Engineering 53 3 2002 209 220 (Pubitemid 34506121)
15. W.C. Chen, A.H.I. Lee, W.J. Deng, and K.Y. Liu The implementation of neural network for semiconductor PECVD process Expert Systems with Applications 32 4 2007 1148 1153 (Pubitemid 44821804)
16. W.C. Chen, S.S. Tseng, and C.Y. Wang A novel manufacturing defect detection method using association rule mining techniques Expert Systems with Applications 29 4 2005 807 815
17. R.P. Cherian, P.S. Midha, and A.G. Pipe Modeling the relationship between process parameters and mechanical properties using bayesian neural networks for powder metal parts International Journal of Production Research 38 10 2000 2201 2214 (Pubitemid 35401846)
18. T.L. Chiang, C.T. Su, T.S. Li, and R.C.C. Huang Improvement of process capability through neural networks and robust design: A case study Quality Engineering 14 2 2002 313 318
19. C. Chien, H. Li, and A. Jeang Data mining for improving the solder bumping process in the semiconductor packaging industry Intelligent Systems in Accounting, Finance and Management 14 1-2 2006 43 57
20. C.F. Chien, W.C. Wang, and J.C. Cheng Data mining for yield enhancement in semiconductor manufacturing and an empirical study Expert Systems with Applications 33 1 2007 192 198
21. I.G. Chong, S.L. Albin, and C.H. Jun A data mining approach to process optimization without an explicit quality function IIE Transactions 39 8 2007 795 804 (Pubitemid 46876940)
22. D.F. Cook, C.T. Ragsdale, and R.L. Major Combining a neural network with a genetic algorithm for process parameter optimization Engineering Applications of Artificial Intelligence 13 4 2000 391 396
23. T. Cool, H.K.D.H. Bhadeshia, and D.J.C. Mackay The yield and ultimate tensile strength of steel welds Materials Science and Engineering A A223 1-2 1997 186 200 (Pubitemid 127421598)
24. L. Cser, J. Gulyas, L. Szucs, A. Horvath, L. Arvai, and B. Baross Different kinds of neural networks in control and monitoring of hot rolling mill Proceedings of the 14th international conference on industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems, IEA/AIE 2001, 4-7 June 2001 Budapest Hungary L. Monostori, J. Vancza, M. Ali, Lecture notes in computer science Vol. 2070 2001 Springer-Verlag London 791 796 (Pubitemid 33291391)
25. F. Cus, and J. Balic Optimization of cutting process by GA approach Robotics and Computer Integrated Manufacturing 19 1-2 2003 113 121
26. C. Da Cunha, B. Agard, and A. Kusiak Data mining for improvement of production quality International Journal of Production Research 44 18/19 2006 4027 4041 (Pubitemid 44181135)
27. T. Dasu, and T. Johnson Exploratory data mining and data cleaning 2003 Wiley-Interscience New York
28. N. De Abajo, A.B. Diez, V. Lobato, and S.R. Cuesta ANN quality diagnostic models for packaging manufacturing: an industrial data mining case study R. Kohavi, KDD-2004: Proceedings of the tenth ACM SIGKDD international conference on knowledge discovery and data mining, 22-25 August 2004 Seattle Washington 2004 ACM Press New York 799 804 (Pubitemid 40115010)
29. Deng, B., & Liu, X. (2002). Data mining in quality improvement. SUGI27: Proceedings of the twenty-seventh annual SAS® users group international conference, 14-17 April 2002 Orlando, Florida [online]. Available from: http://www2.sas.com/proceedings/sugi27/Proceed27.pdf Accessed 23.03.2008.
30. Dhond, A., Gupta, A., & Vadhavkar, S. (2000). Data mining techniques for optimizing inventories for electronic commerce. In S.J. proceedings of the sixth ACM SIGKDD international conference on knowledge discovery and data mining, KDD 2000 (pp. 480-486), 20-23 August. Boston. New York: ACM.
31. M.H. Dunham Data mining introductory and advanced topics 2003 Prentice Hall/Pearson Education New Jersey
32. T. Erzurumlu, and H. Oktem Comparison of response surface model with neural network in determining the surface quality of moulded parts Materials and Design 28 2 2007 459 465 (Pubitemid 44615912)
33. Y. Fasser, and D. Brettner Management for quality in high-technology enterprises 2002 Wiley-Interscience New York
34. U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth The KDD process for extracting useful knowledge from volumes of data Communication of ACM 39 11 1996 27 34 (Pubitemid 126428076)
35. C.X.J. Feng, and X.F. Wang Surface roughness predictive modeling: Neural networks versus regression IIE Transactions on Design and Manufacturing 35 1 2003 11 27
36. C.X.J. Feng, and A. Kusiak Data mining applications in engineering design, manufacturing and logistics International Journal of Production Research 44 14 2006 2689 2694 (Pubitemid 43862181)
37. C.X.J. Feng, and X. Wang Development of empirical models for surface roughness prediction in finish turning International Journal of Advanced Manufacturing Technology 20 5 2002 348 356
38. C.X.J. Feng, and X.F.D. Wang Data mining techniques applied to predictive modeling of the knurling process IIE Transactions 36 3 2004 253 263
39. L.M. Fu Neural networks in computer intelligence 1994 McGraw-Hill New York
40. R. Ganesan, T.K. Das, and V. Venkataraman Wavelet-based multiscale statistical process monitoring: A literature review IIE Transactions 36 9 2004 787 806
41. Gardner, M., & Bieker, J. (2000). Data mining solves tough semiconductor manufacturing problems. In S.J. Proceedings of the sixth ACM SIGKDD international conference on knowledge discovery and data mining, KDD 2000 (pp. 376-383), 20-23 August, Boston. New York: ACM.
42. P. Georgilakis, and N. Hatziargyriou On the application of artificial intelligence techniques to the quality improvement industrial processes Proceedings of the second hellenic conference on AI: Methods and applications of artificial intelligence, 11-12 April, Thessaloniki, Greece I.P. Vlahavas, C.D. Spyropoulos, Lecture notes in computer science Vol. 2308 2002 Springer-Verlag London 473 484
43. P. Giudici Applied data mining: Statistical methods for business and industry 2003 J. Wiley New York
44. M. Goebel, and L. Gruenwald A survey of data mining and knowledge discovery software tools SIGKDD Explor. Newsl. 1 1 1999 20 33
45. S. Guessasma, Z. Salhi, G. Montavon, P. Gougeon, and C. Coddet Artificial intelligence implementation in the APS process diagnostic Materials Science and Engineering B 110 3 2004 285 295
46. M. Hamedi, M. Shariatpanahi, and A. Mansourzadeh Optimizing spot welding parameters in a sheet metal assembly by neural networks and genetic algorithm Proceedings of the Institution of Mechanical Engineers Part B-Journal of Engineering Manufacture 221 7 2007 1175 1184 (Pubitemid 350232160)
47. J. Han, and M. Kamber Data mining: Concepts and techniques 2006 Morgan Kaufmann Publishers San Francisco
48. L. Han, L. Han, and C. Liu Neural network applied to prediction of the failure stress for a pressurized cylinder containing defects International Journal of Pressure Vessels and Piping 76 4 1999 215 219 (Pubitemid 29347942)
49. H. Hand, H. Mannila, and P. Smyth Principles of data mining 2001 MIT Press Cambridge, Mass
50. J.A. Harding, M. Shahbaz, S. Srinivas, and A. Kusiak Data mining in manufacturing: A review Journal of Manufacturing Science and Engineering-Transactions of ASME 128 4 2006 969 976 (Pubitemid 44770144)
51. D. Haughton, J. Deichmann, A. Eshghi, S. Sayek, N. Teebagy, and H. Topi A review of software packages for data mining The American Statistician 57 4 2003 290 309 (Pubitemid 37424484)
52. S.-G. He, L. Li, and E.-S. Qi Study on the quality improvement of injection molding in LED packaging processes based on DOE and data mining Proceedings of the wireless communications, networking and mobile computing WICom 2007, 21-25 September 2007 Shanghai China 2007 IEEE Con. Pub. 6625 6628
53. G.T.S. Ho, H.C.W. Lau, C.K.M. Lee, A.W.H. Ip, and K.F. Pun An intelligent production workflow mining system for continual quality enhancement Intelligent Journal of Advanced Manufacturing Technology 28 7-8 2006 792 809
54. S. Ho, K. Lee, S. Chen, and S. Ho Accurate modeling and prediction of surface roughness by computer vision in turning operations using an adaptive neurofuzzy inference system International Journal of Machine Tools and Manufacture 42 13 2002 1441 1446
55. M. Holena, and M. Baerns Feedforward neural networks in catalysis - A tool for the approximation of the dependency of yield on catalyst composition, and for knowledge extraction Catalysis Today 81 3 2003 485 494
56. T.H. Hou, and C.C. Huang Application of fuzzy logic and variable precision rough set approach in a remote monitoring manufacturing process for diagnosis rule induction Journal of Intelligent Manufacturing 15 3 2004 395 408
57. T.H. Hou, W.L. Liu, and L. Lin Intelligent remote monitoring and diagnosis of manufacturing processes using an integrated approach of neural networks and rough sets Journal of Intelligent Manufacturing 14 2 2003 235 239
58. K.L. Hsieh, and L.I. Tong Optimization of multiple quality responses involving qualitative and quantitative characteristics in IC manufacturing using neural networks Computers in Industry 46 1 2001 1 12
59. S.C. Hsu, and C.F. Chien Hybrid data mining approach for pattern extraction from wafer bin map to improve yield in semiconductor manufacturing International Journal of Production Economics 107 1 2007 88 103
60. C. Hu, and S. Su Hierarchical clustering methods for semiconductor manufacturing data Proceedings of the IEEE international conference on networking, sensing and control, 21-23 March 2004 Taipei, Taiwan Vol. 2 2004 IEEE 1063 1068
61. C. Huang, T. Li, and T. Peng Attribute selection based on rough set theory for electromagnetic interference (EMI) fault diagnosis Quality Engineering 18 2 2006 161 171
62. H. Huang, and D. Wu Product quality improvement analysis using data mining: A case study in ultra-precision manufacturing industry Fuzzy systems and knowledge discovery, proceedings of the second international conference on fuzzy systems and knowledge discovery, FSKD 2005, 22-29 August 2005 Changsha China L. Wang, Y. Jin, Lecture notes in computer science Vol. 3614 2005 Springer Berlin 577 580 (Pubitemid 41480129)
63. Y.H. Hung Optimal process parameters design for a wire bonding of ultra-thin CSP package based on hybrid methods of artificial intelligence Microelectronics International 24 3 2007 3 10
64. M.A. Hussain Review of the applications of neural networks in chemical process control - Simulation and online implementation Artificial Intelligence in Engineering 13 1 1999 55 68
65. A.A. Ilumoka A modular neural network approach to microelectronic circuit yield optimization Microelectronics Reliability 38 4 1998 571 580 (Pubitemid 128635593)
66. International Standard Industrial Classification of All Economic Activities, Revision 4, Section C - Manufacturing (10 February (2009). http://unstats.un.org/unsd/cr/registry/regcst.asp?Cl=27, United Nations.
67. K.W. Ip, C.K. Kwong, and Y.W. Wong Fuzzy regression approach to modeling transfer moulding for microchip encapsulation Journal of Materials Processing Technology 140 1-3 2003 147 151
68. G.T. Jemwa, and C. Aldrich Improving process operations using support vector machines and decision trees AICHE Journal 51 2 2005 526 543 (Pubitemid 40321682)
69. Y. Jiao, S. Lei, Z.J. Pei, and E.S. Lee Fuzzy adaptive networks in machining process modeling: Surface roughness prediction for turning operations International Journal of Machine Tools and Manufacture 44 15 2004 1643 1651
70. B.S. Kang, D.H. Choe, and S.C. Park Intelligent process control in manufacturing industry with sequential processes International Journal of Production Economics 1999 583 590
71. M.A. Karim, S. Halgamuge, A.J.R. Smith, and A.L. Hsu Manufacturing yield improvement by clustering Neural information processing: 13th international conference proceedings Part III, 3-6 October 2006 Hong Kong China I. King, LNCS Vol. 4234 2006 Springer Berlin 526 534 (Pubitemid 44699891)
72. S.R. Karnik, V. Gaitonde, and J.P. Davim Integrating Taguchi principle with genetic algorithm to minimize burr size in drilling of AISI 316L stainless steel using an artificial neural network model Proceedings of the Institution of Mechanical Engineers Part B-Journal of Engineering Manufacture 221 12 2007 1695 1704
73. Kartal, E. (2007). Metamodeling complex systems using linear and nonlinear regression methods. Unpublished Master of Science Thesis, Middle East Technical University, Ankara, Turkey.
74. E.S. Kim, C. Oh, S. Lee, B. Lee, and I. Yun Modeling and optimization of process parameters for GaAs/AlGaAs multiple quantum well avalanche photodiodes using genetic algorithms Microelectronics Journal 32 7 2001 563 567 (Pubitemid 32518207)
75. I. Kim, J. Son, and P.K.D.V. Yarlagadda A study on the quality improvement of robotic GMA welding process Robotics and Computer Integrated Manufacturing 19 6 2003 567 572
76. S.H. Kim, and C.M. Lee Nonlinear prediction of manufacturing systems through explicit and implicit data mining Computer and Industrial Engineering 33 3-4 1997 461 464 (Pubitemid 127406823)
77. W.J. Kolarik Creating quality: Concepts, systems, strategies, and tools 1995 McGraw-Hill New York
78. G. Köksal, W.A. Smith Jr., Y. Fathi, J.C. Lu, and R. McGregor A case study in off-line quality control: Characterization and optimization of batch dyeing process design International Journal of Technology Management: Special Issue on Total Quality Management 16 4/5/6 1998 358 382 (Pubitemid 128639597)
79. Köksal, G., Batmaz,., & Testik, M. C. (2008). Data mining processes and a review of their applications for product and process quality improvement in manufacturing industry. Technical Report No: 08-03, Industrial Engineering Department, Middle East Technical University, Ankara.
80. A. Krimpenis, P.G. Benardos, G.C. Vosniakos, and A. Koukouvitaki Simulation-based selection of optimum pressure die-casting process parameters using neural nets and genetic algorithms International Journal of Advances Manufacturing Technology 27 5-6 2006 509 517 (Pubitemid 41744278)
81. H. Kurtaran, B. Ozcelik, and T. Erzurumlu Warpage optimization of a bus ceiling lamb base using neural network model and genetic algorithm Journal of Materials Processing Technology 169 2 2005 314 319 (Pubitemid 41425763)
82. A. Kusiak, and C. Kurasek Data mining of printed-circuit board defects IEEE Transactions on Robotics and Automation 17 2 2001 191 196 (Pubitemid 32609737)
83. A. Kusiak Decomposition in data mining: An industrial case study IEEE Transactions on Electronics Packaging Manufacturing 23 4 2000 345 354
84. A. Kusiak A data mining approach for generation of control signatures Journal of Manufacturing Science and Engineering-Transactions of the ASME 124 4 2002 923 926 (Pubitemid 35384312)
85. A. Kusiak Data mining: Manufacturing and service applications International Journal of Production Research 44 18/19 2006 4175 4191 (Pubitemid 44181144)
86. Y. Kwon, O.A. Omitaomu, and G.N. Wang Data mining approaches for modeling complex electronic circuit design activities Computers & Industrial Engineering 54 2008 229 241 (Pubitemid 350216234)
87. M. Last, and A. Kandel Data mining for process and quality control in the semiconductor industry D. Braha, Data mining for design and manufacturing 2001 Kluwer Academic Publishers Dordrecht 207 234
88. S.H. Lee, and D.A. Dornfeld Prediction of burr formation during face milling using an artificial neural network with optimized cutting conditions Proceedings of the Institution of Mechanical Engineers Part B-Journal of Engineering Manufacture 221 12 2007 1705 1714
89. R.W. Lewis, and R.S. Ransing A semantically constrained bayesian network for manufacturing diagnosis International Journal of Production Research 35 8 1997 2171 2187 (Pubitemid 127549718)
90. T.S. Li, C.L. Huang, and Z.Y. Wu Data mining using genetic programming for construction of a semiconductor manufacturing yield rate prediction system Journal of Intelligent Manufacturing 17 2006 355 361
91. T.S. Li, C.T. Su, and T.L. Chiang Applying robust multi-response quality engineering for parameter selection using a novel neural-genetic algorithm Computers in Industry 50 1 2003 113 122
92. M. Li, S. Feng, I.K. Sethi, J. Luciow, and K. Wagner Mining production data with neural network and CART Proceedings of the third IEEE international conference on data mining (ICDM 2003), 19-22 November 2003 Melbourne FL 2003 IEEE 731 734
93. J. Lian, X.M. Lai, Z.Q. Lin, and F.S. Yao Application of data mining and process knowledge discovery in sheet metal assembly dimensional variation diagnosis Journal of Materials Processing Technology 129 1-3 2002 315 320
94. T.W. Liao, Z.H. Zhan, and C.R. Mount An integrated database and expert system for failure mechanism identification: Part I - Automated knowledge acquisition Engineering Failure Analysis 6 6 1999 387 406
95. T.W. Liao, Z.H. Zhan, and C.R. Mount An integrated database and expert system for failure mechanism identification: Part II - The system and performance testing Engineering Failure Analysis 6 6 1999 407 421
96. C.L. Lin, J.L. Lin, and T.C. Ko Optimization of the EDM process based on the orthogonal array with fuzzy logic and grey relational analysis method International Journal of Advanced Manufacturing Technology 19 4 2002 271 277 (Pubitemid 34268707)
97. J.L. Lin, K.S. Wang, B.H. Yan, and Y.S. Tarng Optimization of the electrical discharge machining process based on the Taguchi method with fuzzy logics Journal of Materials Processing Technology 102 1-3 2000 48 55
98. W.S. Lin, and K.S. Wang Modelling and optimization of turning processes for slender parts International Journal of Production Research 38 3 2000 587 606 (Pubitemid 35395466)
99. X. Liu, H. Tang, Z. Fan, and B. Deng Quality improvement modeling and practice in baosteel based on KIV-KOV analysis Advances in web-age information management: 5th international conference, WAIM 2004, 15-17 July 2004 Dalian, China Q. Li, G. Wang, L. Feng, Lecture Notes in Computer Science Vol. 3129 2004 Springer-Verlag Berlin 720 725
100. H.H. Lou, and Y.L. Huang Hierarchical decision making for proactive quality control: System development for detect reduction in automotive coating operations Engineering Applications of Artificial Intelligence 16 3 2003 237 250
101. J.C. Lu Methodology of mining massive data sets for improving manufacturing quality/efficiency D. Braha, Data mining for design and manufacturing: Methods and applications 2001 Kluwer Academic Publishers Dordrecht 255 288
102. D.W. Lu, and J. Antony Optimization of multiple responses using a fuzzy-rule based inference system International Journal of Production Research 40 7 2002 1613 1625 (Pubitemid 34598636)
103. O. Maimon, and L.S. Rokach Data mining by attribute decomposition with semiconductor manufacturing case study D. Braha, Data mining for design and manufacturing 2001 Kluwer Academic Publishers Dordrecht 311 336
104. W.L. Martinez, and A.R. Martinez Computational statistics handbook with MATLAB 2002 Chapman and Hall Boca Raton
105. P.G. Mathews, and M.S. Shunmugam Neural-network approach for predicting hole quality in reaming International Journal of Machine Tools & Manufacture 39 5 1999 723 730
106. T.K. Meng, and C. Butler Solving multiple response optimisation problems using adaptive neural networks International Journal of Advanced Manufacturing Technology 13 9 1997 666 675
107. F. Mieno, T. Sato, Y. Slubnya, K. Odagiri, H. Tsuda, and K. Take Yield improvement using data mining system Semiconductor manufacturing conference proceedings, 1999 IEEE international symposium on, 11-13 October Santa Clara CA 1999 IEEE 391 394 (Pubitemid 30515961)
108. D. Montgomery Introduction to statistical quality control 2005 John Wiley Hoboken, NJ
109. T.S. Newman, and A.K. Jain A survey of automated visual inspection Computer Vision, Graphics and Image Processing 61 2 1995 231 262
110. 2 laser welding Advances in Engineering Software 37 10 2006 643 648 (Pubitemid 44108648)
111. J.B. Ordieres Meré, A. González Marcos, J.A. González, and V. Lobato Rubio Estimation of mechanical properties of steel strip in hot dip galvanising lines Ironmaking and Steelmaking 31 1 2004 43 50 8
112. B. Ozcelik, and T. Erzurumlu Comparison of the warpage optimization in the plastic injection molding using ANOVA, neural network model and genetic algorithm Journal of Materials Processing Technology 171 3 2006 437 445 (Pubitemid 43106623)
113. M. Perzyk, R. Biernacki, and A. Kochanski Modeling of manufacturing processes by learning systems: The naive bayesian classifier versus artificial neural networks Journal of Materials Processing Technology 164-165 2005 1430 1435 (Pubitemid 40584562)
114. M.S. Phadke Quality engineering using robust design 1989 Prentice-Hall Englewood Cliffs, NJ
115. D.T. Pham, and A.A. Afify Machine-learning techniques and their applications in manufacturing Proceedings of the Institution of Mechanical Engineers Part B-Journal of Engineering Manufacture 219 5 2005 395 412 (Pubitemid 40929803)
116. D.T. Pham, and R.J. Alcock Smart inspection systems: Techniques and applications of intelligent vision 2003 Academic Press Amsterdam, Boston
117. D. Pyle Data preparation for data mining 1999 Morgan Kaufmann Publishers San Francisco, CA
118. R. Rallo, J. Ferre-Gine, A. Arenas, and F. Giralt Neural virtual sensor for the inferential prediction of product quality from process variables Computers and Chemical Engineering 26 12 2002 1735 1754 (Pubitemid 35303612)
119. Rexer Analytics (2008). Available from: http://www.rexeranalytics.com/ Data-Miner-Survey-Results-2008.html.
120. C. Riverol, and J. Cooney Estimation of the ester formation during beer fermentation using neural networks Journal of Food Engineering 82 4 2007 585 588 (Pubitemid 46736002)
121. L. Rokach, and O. Maimon Data mining for improving the quality of manufacturing: A feature set decomposition approach Journal of Intelligent Manufacturing 17 3 2006 285 299
122. B.H.M. Sadeghi A BP-neural network predictor model for plastic injection molding process Journal of Materials Processing Technology 103 3 2000 411 416
123. H. Sarimveis, P. Doganis, and A. Alexandridis A classification technique based on radial basis function neural networks Advances in Engineering Software 37 4 2006 218 221 (Pubitemid 41795661)
124. Y.M. Sebzalli, and X.Z. Wang Knowledge discovery from process operational data using PCA and fuzzy clustering Engineering Applications of Artificial Intelligence 14 5 2001 607 616 (Pubitemid 34182388)
125. M. Shahbaz, S. Srinivas, J.A. Harding, and M. Turner Product design and manufacturing process improvement using association rules Proceedings of the Institution of Mechanical Engineers Part B-Journal of Engineering Manufacture 220 2 2006 243 254 (Pubitemid 46603527)
126. Q. Shao, R.C. Rowe, and P. York Comparison of neurofuzzy logic and decision trees in discovering knowledge from experimental data of an immediate release tablet formulation European Journal of Pharmaceutical Sciences 31 2 2007 129 136 (Pubitemid 46660582)
127. C. Shen, L. Wang, and Q. Li Optimization of injection molding process parameters using combination of artificial neural network and genetic algorithm method Journal of Materials Processing Technology 183 2-3 2007 412 418 (Pubitemid 46209648)
128. X. Shi, P. Schillings, and D. Boyd Applying artificial neural networks and virtual experimental design to quality improvement of two industrial processes International Journal of Production Research 42 1 2004 101 118
129. K.R. Skinner, D.C. Montgomery, G.C. Runger, J.W. Fowler, D.R. McCarville, and T.R. Rhoads Multivariate statistical methods for modeling and analysis of wafer probe test data IEEE Transactions on Semiconductor Manufacturing 15 4 2002 523 530
130. T.S. Suneel, S.S. Pandle, and P.P. Date A technical note on integrated product quality model using artificial neural networks Journal of Materials Processing Technology 121 1 2002 77 86 (Pubitemid 34116165)
131. B.S. Sung, I.S. Kim, Y. Xue, H.H. Kim, and Y.H. Cha Fuzzy regression model to predict the bead geometry in the robotic welding process ACTA Metallurgica Sinica 20 6 2007 391 397
132. G. Taguchi, S. Chowdhury, and S. Taguchi Robust engineering 2000 McGraw-Hill New York
133. C.M. Tam, T.K.L. Tong, T.C.T. Lau, and K.K. Chan Diagnosis of prestressed concrete pile defects using probabilistic neural networks Engineering Structures 26 8 2004 1155 1162 (Pubitemid 38791049)
134. K.M. Tay, and C. Butler Modelling and optimizing of a MIG welding process - A case study using experimental designs and neural networks Quality and Reliability Engineering International 13 2 1997 61 70 (Pubitemid 127623239)
135. S.Y. Teng, and S.J. Hwang Predicting the process induced warpage of electronic packages using the P-V-T-C equation and the Taguchi method Microelectronics Reliability 47 12 2007 2231 2241
136. Y.H. Tsai, J.C. Chen, and S. Lou An in-process surface recognition system based on neural networks in end milling cutting operations International Journal of Machine Tools and Manufacture 39 4 1999 583 605
137. C.Y. Tsai, C.C. Chiu, and J.S. Chen A case-based reasoning system for PCB defect prediction Expert Systems with Applications 28 2005 813 822
138. H.Y. Tseng Welding parameters optimization for economics design using neural approximation and genetic algorithm International Journal of Advanced Manufacturing Technology 27 9/10 2006 897 901
139. T.B. Tseng, Y. Kwon, and Y.M. Ertekin Feature-based rule induction in machining operation using rough set theory for quality assurance Robotics and Computer-integrated Manufacturing 21 6 2005 559 567 (Pubitemid 41084238)
140. T.L. Tseng, M.C. JothiShankar, and T. Wu Quality control problems in printed circuit board manufacturing - An extended rough set theory approach Journal of Manufacturing Systems 23 1 2004 56 72 (Pubitemid 40415395)
141. Tseng, T. L., JothiShankar, M. C., Wu, T., Xing, G., & Jiang, F. (2004b). Applying data mining approaches for defect diagnosis in manufacturing industry. IERC 2004, Houston, TX, 7.
142. Tseng, T. L., Leeper, T., Banda, C., Herren, S. M., & Ford, J. (2004c). Quality assurance in machining process using data mining. IERC 2004, Houston, TX, 6.
143. Tsuda, H., Shirai, H., Takagi, O., Take, R. (2000). Yield analysis and improvement by reducing manufacturing fluctuation noise. In Proceedings of International Symposium on Semiconductor Manufacturing (ISSM 2000), 26-28 September Tokyo. 249-252.
144. D. Umbrello, G. Ambogio, L. Filice, and R. Shivpuri An ANN approach for predicting subsurface residual stresses and the desired cutting conditions during hard turning Journal of Materials Processing Technology 189 1-3 2007 143 152 (Pubitemid 46529192)
145. M. Vasudevan, B.P.C. Rao, B. Venkatraman, T. Jayakumar, and B. Raj Artificial neural network modeling for evaluating austenitic stainless steel and Zircaloy-2 welds Journal of Materials Processing Technology 169 3 2005 396 400 (Pubitemid 41430379)
146. M. Vasudevan, M. Murugananth, and A.K. Bhaduri Application of bayesian neural network for modeling and prediction of ferrite number in austenitic stainless steel welds H. Cerjak, H.K.D.H. Bhadeshia, Mathematical modeling of weld phenomena-VI 2002 The Institute of Materials London 1079 1099
147. G.C. Vosniakos, T. Maroulis, and D. Pantelis A method for optimizing process parameters in layer-based rapid prototyping Proceedings of the Institution of Mechanical Engineers Part B-Journal of Engineering Manufacture 221 8 2007 1329 1340 (Pubitemid 350232149)
148. K. Wang Applying data mining to manufacturing: the nature and implications Journal of Intelligent Manufacturing 18 2007 487 495 (Pubitemid 47191452)
149. Wang, K., Tong, S., Eynard, B., Roucoules, L., & Matta, N. (2007a). Review on application of data mining in product design and manufacturing. In Lei, J., Yu, J., Zhou, S. (Eds.), Proceedings of the fourth international conference on fuzzy systems and knowledge discovery (FSKD 2007), 24-27 August 2007Haikou Hainan, China. IEEE (pp. 613-618). (Pubitemid 351711109)
150. L. Wang, J.C. Fang, Z.Y. Zhao, and H.P. Zeng Application of backward propagation network for forecasting hardness and porosity of coatings by plasma spraying Surface and Coating Technology 201 9-11 2007 5085 5089 (Pubitemid 46158565)
151. R. Wang, L. Wang, L. Zhao, and Z. Liu Influence of process parameters on part shrinkage in SLS Intelligent Journal of Advanced Manufacturing Technology 33 5-6 2006 498 504
152. C.P. Wei, S. Piramuthu, and M.J. Shaw Knowledge discovery and data mining C.W. Holsapple, Handbook on Knowledge Management Vol. 2 2003 Springer-Verlag Berlin 157 189
153. I.H. Witten Data mining: Practical machine learning tools and techniques 2005 Morgan Kaufman Boston, MA
154. Y. Xue, I.S. Kim, J.S. Son, C.E. Park, H.H. Kim, and B.S. Sung Fuzzy regression method for prediction and control the bead width in the robotic arc-welding process Journal of Materials Processing Technology 164 2005 1134 1139 (Pubitemid 40584523)
155. K. Yang, and J. Trewn Multivariate statistical methods in quality management 2004 McGraw-Hill New York
156. T. Yang, and T. Tsai Modeling and implementation of a neurofuzzy system for surface mount assembly defect prediction and control IIE Transactions 34 7 2002 637 646 (Pubitemid 34414734)
157. T. Yang, T. Tsai, and J. Yeh A neural network-based prediction model for fine pitch stencil printing quality in surface mount assembly Engineering Applications of Artificial Intelligence 18 3 2005 335 341 (Pubitemid 40339982)
158. X. Yin, and W. Yu The virtual manufacturing model of the worsted yarn based on artificial neural networks and grey theory Applied Mathematics and Computation 185 1 2006 322 332
159. L. Zhai, L. Khoo, and S. Fok Feature extraction using rough set theory and genetic algorithms - An application for the simplification of product quality evaluation Computers and Industrial Engineering 43 4 2002 661 676 (Pubitemid 34991782)
160. J.H. Zhang, A.G. Xie, and F.M. Shen Multi-objective optimization and analysis model of sintering process based on BP neural network Journal of Iron and Steel Research, International 14 2 2007 01 05
161. C. Zhou, P.C. Nelson, W. Xiao, T.M. Tripak, and S.A. Lane An intelligent data mining system for drop test analysis of electronic products IEEE Transactions on Electronics Packaging Manufacturing 24 3 2001 222 231 (Pubitemid 33047919)
162. Q. Zhou, Z. Xiong, J. Zhang, and Y. Xu Hierarchical neural network based product quality prediction of industrial ethylene pyrolysis process Proceedings of the third international symposium on neural networks, advances in neural networks (ISNN 2006) J. Wang, Lecture Notes in Computer Science, 28 May - 1 June, 2006 Chengdu China Vol. 3973 2006 Springer-Verlag Berlin 1132 1137 (Pubitemid 44045835)
163. F. Zorriassatine, and J.D.T. Tannock A review of neural networks for statistical process control Journal of Intelligent Manufacturing 9 3 1998 209 224
164. U. Zuperl, and F. Cus Optimization of cutting conditions during cutting by using neural networks Robotics and Computer-Integrated Manufacturing 19 1-2 2003 189