Applications of neural networks in manufacturing: a state-of-the-art survey

References

• ALI , D. L. , and KAMAL , S. , 1990 , The undeterministic manipulation of solid models for robot program synthesis . Computers & Industrial Engineering , 19 , 465 – 468 .
   Web of Science ®Google Scholar
• ANDERSON , K. , COOK , G. E. , and GABOR , K. , 1990 , Artifical neural networks applied to arc welding process modelling and control . IEEE Transactions on Industry Applications, 26 , 824 – 830 .
   Web of Science ®Google Scholar
• ANDERSON , K. , COOK , G. E. , SPRINGFIELD , J. F. , and BARNETT , R. J. , 1991 , Applications of artificial neural networks for arc welding . In Intelligent Engineering Systems Through Artificial Neural Networks , C. H. Dagli, S. R. T. Kumara, and Y. C Shin $$eds$$ ( New York ASME ), pp. 717 – 728 .
   Google Scholar
• ARAI , E. , and IWATA , K. , 1990 , CAD with design specification decomposition and its application . Annals of the CIRP , 39 ( 1 ), 121 – 124 .
   Google Scholar
• ARIZONO , L. , YAMAMOTO , A. , and OHTA , H. , 1992 , Scheduling for minimizing total actual flow time by neural networks . International Journal of Production Research , 30 ( 3 ), 503 – 511 .
   Web of Science ®Google Scholar
• BADIRU , A. B. , 1990 , Artificial intelligence applications in manufacturing . In The Automated Factory Handbook Technology and Management , D. I. Cleland and B. Bidanda $$eds$$ ( New York TAB Professional and Books ), pp. 496 – 526 .
   Google Scholar
• BARSCHDORFF , D. , 1990 , Case studies in adaptive fault diagnosis using neural networks . Proceedings of the IMACS Annals on Computing and Applied Mathematics , 3 – 7 Sept ., Brussels .
   Google Scholar
• BARSCHDORFF , D. , and MONOSTORI , L. , 1991 , Neural networks their applications and perspectives in intelligent machining . Computers in Industry , 17 , 101 – 119 .
   Web of Science ®Google Scholar
• BARSCHDORFF , D. , MONOSTORI , A. F. , NDENGE , A. F. , and WOSTENKUHLER , G. W. , 1991 , Multiprocesor systems for connectionist diagnosis of technical processes . Computers in Industry , 17 ( 2,3 ), 131 – 145 .
   Web of Science ®Google Scholar
• BAUER , C M. , 1991 , NAMRC XIX report . Manufacturing Engineering , 107 , 55 – 58 .
   Web of Science ®Google Scholar
• BEN-DAVID , A. , and PAO , Y.-H. , 1992 , Self-improving expert systems an architecture and implementation . Information & Management , 22 , 323 – 331 .
   Web of Science ®Google Scholar
• BURKE , L. I. , and RANGWALA , S. , 1991 , Tool condition monitoring in metal cutting a neural network approach . Journal of Intelligent Manufacturing , 2 ( 5 ), 269 – 280 .
   Web of Science ®Google Scholar
• CAUDILL , M. , 1987 , Neural networks primer part I . AI Experts , 2 ( 12 ), 46 – 52 .
   Google Scholar
• CHANG , T. C. , 1990 , Expert Process Planning for Manufacturing ( MA Addison-Wesley ).
   Google Scholar
• CHEN , C. L. P. , and YAN , Q.-W. , 1991 , Design of a case associative assembly planning system . In Intelligent Engineering Systems Through Artificial Neural Networks , C. H. Dagli, S. R. T. Kumara, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 757 – 762 .
   Google Scholar
• CHEN , C. L. P. , 1992 , Design of a real-time AND/OR assembly scheduler on an optimization neural network . Journal of Intelligent Manufacturing , 3 ( 4 ), 251 – 262 .
   Web of Science ®Google Scholar
• CHEN , C. L. P. , 1993 , Setup generation and feature sequencing using unsupervised learning algorithm . In Proceedings of the 1993 NSF Design and Manufacturing Systems Conference , 6 – 8 January , Charlotte , North Carolina .
   Google Scholar
• CHOVAN , J. D. , and WALDRON , M. B. , 1991 , Towards intelligent CAD a neural network model of the transformation from perception to function in mechanical engineering design . In Intelligent Engineering Systems Through Artificial Neural Networks , C. H. Dagli, S. R. T. Kumara, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 751 – 756 .
   Google Scholar
• CHOW , M.-V. , MANGUM , P. M. , and YEE , S. O. , 1991 , A neural network approach to real-time condition monitoring of induction motors . IEEE Transactions on Industrial Electronics , 38 ( 6 ), 449 – 454 .
   Web of Science ®Google Scholar
• CHRYSSOLOURIS , G. , and DOMOROESE , M. , 1988 , Sensor integration for tool wear estimation in machining . Proceedings of the ASME on Sensors and Controls for Manufacturing , WAM , Chicago , Illinois , pp. 115 – 123 .
   Google Scholar
• CHRYSSOLOURIS , G. , and GUILLOT , M. , 1988 , An AI approach to the selection of process parameters in intelligent machining . Proceedings of the ASME on Sensors and Controls for Manufacturing , WAM , Chicago , Illinois .
   Google Scholar
• CHRYSSOLOURIS , G. , LEE , M. , and PIERCE , J. , 1990 , Use of neural networks for the design of manufacturing systems . Manufacturing Review , 3 ( 3 ), 187 – 194 .
   Google Scholar
• CHRYSSOLOURIS , G. , LEE , M. , and DOMOROESE , M. , 1991 , The use of neural networks in determining operational policies for manufacturing systems . Journal of Manufacturing Systems , 10 ( 2 ), 166 – 175 .
   Web of Science ®Google Scholar
• CHRYSSOLOURIS , G. , DOMOROESE , M. , and BEAULLIEU , P. , 1992 , Sensor synthesis for control of manufacturing processes . Journal of Engineering for Industry , 114 , May, 158 – 174 .
   Web of Science ®Google Scholar
• COYNE , R. D. , and POSTMUS , A. G. , 1990 , Spatial application of neural networks in computer-aided design . Artificial Intelligence in Engineering , 5 ( 1 ), 9 – 22 .
   Google Scholar
• DAGLI , C. , and HUGGAHALLI , R. , 1991 , Neural network approach to group technology . In Knowledge-Based Systems and Neural Networks Techniques and Applications , R. Sharda, J. Y. Cheung, and W. J. Cochran $$eds$$ ( New York Elsevier ), pp. 213 – 228 .
   Google Scholar
• DHINGRA , A. K. , and RAO , S. S. , 1992 , A neural network based approach to mechanical design optimization . Engineering Optimization , 20 , 187 – 203 .
   Google Scholar
• DORNKELD , D. A. , 1990 , Unconventional sensors and signal conditioning for automatic supervision . International Conference on Automatic Supervision, Monitoring and Adaptive Control in Manufacturing , Rydzyna , Poland , pp. 197 – 233 .
   Google Scholar
• ELANAYAR , S. , SHIN , Y. C , 1991 , Tool wear estimation in turning operations based on radial basis functions . In Intelligent Engineering Systems Through Artificial Neural Networks, C. H. Dagli, S. R. T. Kumara, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 685 – 692 .
   Google Scholar
• FELDMAN , J. A. , 1990 , Neural networks, artificial intelligence and computational reality . Computers in Industry , 14 , May , 145 – 148 .
   Web of Science ®Google Scholar
• FELDMAN , J. A. , and BALLARD , D. H. , 1982 , Connectionist models and their properties . Cognitive Science , 6 , 205 – 264 .
   Web of Science ®Google Scholar
• Foo , Y. P. S. , and TAKEFUJI , Y. , 1988 , Integer linear programming neural networks for job-shop scheduling . Proceedings of the 1988 International IEEE Conference on Neural Networks , Vol. 2 , San Diego , California , pp. 341 – 348 .
   Google Scholar
• FOOTE , B. L. , TILLINGHAST , T. , TRETHEWAY , S. , CHEUNG , J. Y. , and CHANG , C.-H. , 1990 , Application of neural networks to optimize plant layout problems . In Knowledge-Based Systems and Neural Networks Techniques and Applications , R. Sharda, J. Y. Cheung, and W. J. Cochran $$eds$$ ( New York Elsevier ), pp. 229 – 235 .
   Google Scholar
• GAINES , B. R. , 1986 , Expert systems in manufacturing . AUTOFACT 86. Detroit, Michigan.
   Google Scholar
• GINGRICH , C. G. , KUESPERT , D. R. , and MCAVOY , T. J. , 1992 , Modelling human operators using neural networks . ISA Transactions , 31 ( 3 ), 81 – 90 .
   PubMed Web of Science ®Google Scholar
• GOVEKAR , E. , GRABEC , I. , and PEKLENIK , J. , 1989 , Monitoring of a drilling process by a neural network . The 21st CIRP International Seminar on Manufacturing Systems , Stockholm , Sweden .
   Google Scholar
• GUILLOT , M. , ELOUAFI , A. , 1991 , On-line identification of tool breakage in metal cutting processes by use of neural networks . In Intelligent Engineering Systems Through Artificial Neural Networks, C. H. Dagli, S. R. T. Kumara, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 701 – 710 .
   Google Scholar
• GUHA , A. , 1992 , Continuous process control using neural networks . Journal of Intelligent Manufacturing , 3 ( 4 ), 217 – 228 .
   Web of Science ®Google Scholar
• HALL , J. W. , and Lu , S. C.-Y. , 1991 , An adaptive machine controller utilizing domain knowledge and quantitative data. Annual Report, Knowledge-Based Engineering Systems Research Laboratory , University of Ilinois , pp. 41 – 48 .
   Google Scholar
• HALL , J. W. , and Lu , S. C.-Y. , 1992 , Emulating human process control functions with neural networks. Annual Report, Knowledge-Based Engineering Systems Research Laboratory , University of Illinois , pp. 145 – 152 .
   Google Scholar
• HAM , I. , and Lu , S. C.-Y. , 1988 , Computer-aided process planning the present and the future . Annals of the CIRP , 37 ( 2 ), 1 – 11 .
   Google Scholar
• HATVANY , J. , 1987 , Matching Al tools to engineering requirements . Annals of the CIRP , 36 ( 1 ), 311 – 315 .
   Google Scholar
• HOPFIELD , J. J. , and TANK , D. W. , 1985 , Neural computation of decisions in optimization problem . Biological Cybernetics , 52 , 141 – 152 .
   PubMed Web of Science ®Google Scholar
• HORNE , B. , JAMSHIDI , M. , and VADIEE , N. , 1990 , Neural networks in robotics a survey . Journal of Intelligent and Robotics Systems , 3 , 51 – 66 .
   Web of Science ®Google Scholar
• Hou , T.-H. , and LIN , L. , 1993 , Manufacturing process monitoring using neural networks . Computers and Electrical Engineering , 19 ( 2 ), 129 – 141 .
   Web of Science ®Google Scholar
• JALEL , N. A. , MIRZAI , A. R. , LEIGH , J. R. , and NICHOLSON , H. , 1991 , Application of neural network in process control. In Neural Network Applications, J. G. Taylor (ed) ( London Springer ), pp. 101 – 113 .
   Google Scholar
• KAMARTHI , S. V. , KUMARA , S. T. , YU , F. T. S. , and HAM , I. , 1990 , Neural networks and their applications in component design data retrieval . Journal of Intelligent Manufacturing , 1 ( 2 ), 125 – 140 .
   Web of Science ®Google Scholar
• KAMARTHI , S. V. , COHEN , G. S. , and KUMARA , S. R. T. , 1991 , On-line tool wear monitoring using a Kohonen's feature map . In Intelligent Engineering Systems Through Artificial Neural Networks, C. H. Dagli, S. R. T. Kumara, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 639 – 644 .
   Google Scholar
• KAO , Y. , and MOON , Y. B. , 1990 , Learning part families by the backpropagalion rule of neural networks . Proceedings of the 1st International Conference on Automation Technology , Hsinchu , Taiwan , pp. 819 – 824 .
   Google Scholar
• KAO , Y. , and MOON , Y. B. , 1991 , A unified group technology implementation using the backpropagation learning rule of neural networks . Computers and Industrial Engineering , 20 ( 4 ), 425 – 437 .
   Web of Science ®Google Scholar
• KAPARTHI , S. , and SURESH , N. C. , 1991 , A neural network system for shape-based classification and coding of rotational parts . International Journal of Production Research , 29 ( 9 ), 1771 – 1784 .
   Web of Science ®Google Scholar
• KARSAI , G. , ANDERSON , K. , COOK , G. E. , and BARNETT , R. J. , 1992 , Neural network methods for the modelling and control of welding processes . Journal of Intelligent Manufacturing , 3 ( 4 ), 229 – 236 .
   Web of Science ®Google Scholar
• KENNEDY , M. P. , and CHUA , L. O. , 1988 , Neural networks for nonlinear programming . IEEE Transactions on Circuits and Systems , 35 ( 5 ), 554 – 562 .
   Google Scholar
• KIM , N. , TAKAI , Y. , and KUNII , T. L. , 1992 , Geometrical constraint solving based on the extended Boltzmann machine . Computers in Industry , 19 , 239 – 250 .
   Web of Science ®Google Scholar
• KING , J. R. , and NAKORNCHAI , V. , 1982 , Machine-component group formation in group technology review and extension . International Journal of Production Research , 20 ( 2 ), 117 – 133 .
   Web of Science ®Google Scholar
• KIRRANE , D. E. , 1990 , Machine learning . Training and Development Journal , 40 , 24 – 29 .
   Google Scholar
• KNAPP . G. M. , and WANG , H.-P. , 1992a , Machine fault classification a neural network approach . International Journal of Production Research , 30 ( 4 ), 811 – 823 .
   Web of Science ®Google Scholar
• KNAPP , G. M. , and WANG , H.-P. , 1992b , Acquiring, storing and utilizing process planning knowledge using neural networks . Journal of Intelligent Manufacturing , 3 ( 5 ), 333 – 344 .
   Web of Science ®Google Scholar
• KOHONEN , T. , 1988 , An introduction to neural computing . Neural Networks , 1 , 3 – 16 .
   Web of Science ®Google Scholar
• KOKAR , M. M. , 1989 , Machine learning . In Knowledge-based Systems in Manufacturing , A. Kusiak (ted) ( Pennsylvania Taylor & Francis ), pp. 45 – 81 .
   Google Scholar
• KUMARA , S. R. T. , and HAM , I. , 1990 , Use of associative memory and self-organization in conceptual design . Annals of the CIRP , 39 ( 1 ), 117 – 120 .
   Google Scholar
• KUMARA , S. R. T. , and KAMARTHI , S. V. , 1991 , Function-to-structure transformation in conceptual design an associative memory-based paradigm . Journal of Intelligent Manufacturing , 2 ( 5 ), 281 – 292 .
   Web of Science ®Google Scholar
• KUNCICKY , D. C , HRUSKA , S. I. , LACHER , R. C , 1992 , Hybrid systems the equivalence of the rule-based expert system and artificial neural network inference . International Journal of Expert Systems , 4 ( 3 ), 281 – 297 .
   Google Scholar
• LEE , H. , MALAVE , C. O. , and RAMACHANDRAN , S. , 1992 , A self-organizing neural network approach for the design of cellular manufacturing systems . Journal of Intelligent Manufacturing , 3 ( 5 ), 325 – 332 .
   Web of Science ®Google Scholar
• LEVIN , E. , GEWIRTZMAN , R. , and GIDEON , I. , 1990 , Neural network architecture for adaptive system modelling and control . Neural Networks , 4 (2), 185 .
   Google Scholar
• LIANG , T.-P. , MOSKOWITZ , H. , and YIH , Y. , 1992 , Integrating neural networks and semi-Markov processes for automated knowledge acquisition an application to real-time scheduling . Decision Science , 23 ( 6 ), 1297 .
   Web of Science ®Google Scholar
• LIN , C.-S. , WU , I.-C , and Guo , T.-H. , 1991 , Neural networks for sensor failure detection and data recovery. In Intelligent Engineering Systems Through Artificial Neural Networks, C. H. Dagli, S. R. T. Kumara, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 735 – 740 .
   Google Scholar
• LIPPMANN , R. P. , 1987 , An introduction to computing with neural nets . Acoustics, Speech and Signal Processing Magazine , 4 ( 2 ), 4 – 22 .
   Google Scholar
• Lo , Z.-P. , and BAVARIAN , B. , 1993 , Multiple job scheduling with artificial neural networks . Computer & Electrical Engineering , 19 ( 2 ), 87 – 102 .
   Web of Science ®Google Scholar
• MAA , C. Y. , CHIN , C , and SHANBLATT , M. A. , 1989 , Improved linear programming neural networks . Proceedings of the 31st Midwest Symposium, on Circuits and Systems, Urbana , Illinois , pp. 748 – 751 .
   Google Scholar
• MADEY , G. R. , WEINROTH , J. , and VIJAY , S. , 1992 , Integration of neurocomputing and system simulation for modelling continuous improvement systems in manufacturing . Journal of Intelligent Manufacturing , 3 ( 4 ), 193 – 204 .
   Web of Science ®Google Scholar
• MALAVÉ , C. O. , and RAMACHANDRAN , S. , 1991 , Neural network-based design of cellular manufacturing systems . Journal of Intelligent Manufacturing , 2 ( 5 ), 305 – 314 .
   Web of Science ®Google Scholar
• MASORY , O. , 1991 , Monitoring machining processes using multi-sensor readings fused by artificial neural network . Journal of Materials Processing Technology , 20 ( 1 & 2 ), 231 – 240 .
   Web of Science ®Google Scholar
• MONOSTORI , L. , and NACSA , J. , 1990 , On the application of neural nets in real-time monitoring of machining processes . 22nd CIRP International Seminar on Manufacturing Systems , Enschede , Netherlands .
   Google Scholar
• MOON , Y. B. , and CHI , S. C , 1992 , Generalized part family formation using neural network techniques . Journal of Manufacturing Systems , 11 ( 3 ), 149 – 160 .
   Web of Science ®Google Scholar
• MURPHY , J. H. , and KAGLE , B. J. , 1992 , Neural network recognition of electronic malfunctions . Journal of Intelligent Manufacturing , 3 ( 4 ), 205 – 216 .
   Web of Science ®Google Scholar
• NACSA , J. , and MONOSTORI , L. , 1990 , Real-lime monitoring of machining processes . International Conference on Automatic Supervision, Monitoring, and Adaptive Control in Manufacturing , Rydzyna , Poland , pp. 197 – 233 .
   Google Scholar
• NOAKER . P. M. , 1988 , Smart sensing on the factory floor . Production , 100 , 42 – 48 .
   Google Scholar
• OSAKADA , K. , and YANG , G. B. , NAKAMURA , T. , and MORI , K. , 1990 , Expert system for cold forging process based on FEM simulation . Annals of the CIRP , 39 ( 1 ), 249 – 252 .
   Google Scholar
• OSAKADA , K. , and YANG , G.-B. , 1991a , Neural networks for process planning of cold forging . Annals of the CIRP , 40 ( 1 ), 243 – 246 .
   Google Scholar
• OSAKADA , K. , and YANG , G. , 1991b , Application of neural networks to an expert system for cold forging . International Journal of Machine Tools Manufacturing , 31 ( 4 ), 577 – 587 .
   Web of Science ®Google Scholar
• PORT , O. , 1990 , Adding eagle eyes to those lighting fast computers . Business Week , 3194 , Dec , 60B .
   Google Scholar
• PUGH , G. A. , 1989 , Synthetic neural networks for process control . Computers and Industrial Engineering , 17 , 24 – 26 .
   Web of Science ®Google Scholar
• RABELO , L. C , and ALPTEKIN , S. , 1989 , Integrating scheduling and control functions in computer-integrated manufacturing using artificial intelligence . Computers and Industrial Engineering , 14 , 101 – 106 .
   Web of Science ®Google Scholar
• RAY , A. K. , 1991 , Equipment fault diagnosis a neural network approach . Computers in Industry , 16 , 169 – 178 .
   Web of Science ®Google Scholar
• RAY , A. K. , and MURTY , M. S. S. N. , 1989 , Application of artificial intelligence in maintenance management . Proceedings of the 2nd International Conference on Industrial and Engineering Applications of AI and Expert Systems , ACM Tullahoma , USA , pp. 112 – 118 .
   Google Scholar
• ROBERTS , M. , 1988 , Twelve neural network cliches . AI Expert , 3 ( 8 ), 40 – 46 .
   Google Scholar
• SCHAFFER , G. H. , 1986 , Artificial intelligence a tool for smart manufacturing . American Machinist & Automated Manufacturing , 130 ( 8 ), 83 – 94 .
   Google Scholar
• SCHMERR , L. W. , NUGEN , S. M. , and FOROURAGHI , B. , 1991 , Planning robust design experiments using neural networks and Taguchi methods . In Intelligent Engineering Systems Through Artificial Neural Networks , C. H. Dagli, S. R. T. Kumara, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 829 – 834 .
   Google Scholar
• SHTUB , A. , and ZIMERMAN , Y. , 1991 , Estimating the cost of robotics and manual assembly systems by a neural network . In Intelligent Engineering Systems Through Artificial Neural Networks , C. H. Dagli, S. R. T. Kumara, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 801 – 806 .
   Google Scholar
• SMARTT , H. B. , JOHNSON , J. A. , EINERSON , C. J. , and CORDES , G. A. , 1991 , Development of a connectionist fuzzy logic system for control of gas metal arc welding . In Intelligent Engineering Systems Through Artificial Neural Networks , C. H. Dagli, S. R. T. Kumra, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 711 – 716 .
   Google Scholar
• SMITH , A. E. , 1991 , Quality control using backpropagation an injection molding application . In Intelligent Engineering Systems Through Artificial Neural Networks , C. H. Dagli, S. R. T. Kumara, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 729 – 734 .
   Google Scholar
• SOLIMAN , J. T. , 1987 , Expert systems in manufacturing . Proceedings of the 17th ISATA Conference Keynote Speeches , Munich , Germany .
   Google Scholar
• SORSA , T. , Koivo , H. N. , and KOIVISTO , H. , 1991 , Neural networks in process fault diagnosis . IEEE Transactions on Systems, Man, and Cybernetics , 21 ( 4 ), 815 – 825 .
   Web of Science ®Google Scholar
• SPELT , P. F. , KNEE , H. E. , and GLOVER , C. W. , 1991 , Hybrid artificial intelligence architecture for diagnosis and decision-making in manufacturing . Journal of Intelligent Manufacturing , 2 ( 5 ), 261 – 268 .
   Web of Science ®Google Scholar
• TAFTI , M. H. A. , 1992 , Neural networks a new dimension in expert systems applications . Data Base , Winter , 51 – 54 .
   Google Scholar
• TAGLIARINI , G. A. , CHRIST , J. F. , and PAGE , E. W. , 1991 , Optimization using neural networks . IEEE Transactions on Computers , 40 ( 12 ), 1347 – 1358 .
   Web of Science ®Google Scholar
• TANK , D. W. , and HOPFIELD , J. J. , 1986 , Simple 'neural' optimization networks an A/D converter, signal decision circuit and a linear programming circuit . IEEE Transactions on Circuits and Systems , CAS-33 ( 5 ), 533 – 541 .
   Google Scholar
• UDO , G. J. , 1992 , Neural networks applications in manufacturing processes . Computers and Industrial Engineering , 23 ( 1 – 4 ), 94 – 100 .
   Web of Science ®Google Scholar
• UPADHYAYA , B, R. , and ERYUREK , E. , 1992 , Application of neural networks for sensor validation and plant monitoring . Nuclear Technology , 97 ( 2 ), 170 – 176 .
   Web of Science ®Google Scholar
• VAITHYANATHAN , S. , and IGNIZIO , J. P. , 1992 , A stochastic neural network for resource constrained scheduling . Computers and Operations Research , 19 ( 3, 4 ), 241 – 254 .
   Web of Science ®Google Scholar
• VALLIERE , D. , and LEE , J.-M. , 1988 , Artificial intelligence in manufacturing . Automation , May , 40 – 44 .
   Google Scholar
• VENUGOPAL , V. , and NARENDRAN , T. T. , 1992 , Neural network model for design retrieval in manufacturing systems . Computers in Industry , 20 , 11 – 23 .
   Web of Science ®Google Scholar
• VERDUIN , W. H. , 1992 , The role of integrated AI technologies in product formation . ISA Transactions , 31 ( 2 ), 151 – 157 .
   Web of Science ®Google Scholar
• WANG , J. , and CHANKONG , V. , 1991 , Neurally-inspired stochastic algorithm for determining multi-stage multi-attribute sampling inspection plans . Journal of Intelligent Manufacturing , 2 ( 5 ), 327 – 336 .
   Web of Science ®Google Scholar
• WANG , J. , and MALAKOOTI , B. , 1992 , A feedforward neural network for multiple criteria decision making . Computers and Operations Research , 19 ( 2 ), 151 – 166 .
   Web of Science ®Google Scholar
• WASSERMAN , P. D. , UNAL , A. , and HADDAD , S. , 1991 , Neural networks for on-line machine condition monitoring . In Intelligent Engineering Systems Through Artificial Neural Networks , C.H. Dagli, S. R. T. Kumara, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 693 – 700 .
   Google Scholar
• WIDROW , B. , and LEHR , M. A. , 1990 , 30 years of adaptive neural networks perceptron, Madaline, and backpropagation . Proceedings of the IEEE , 78 (9), 1415 – 1442 .
   Google Scholar
• Wu , H.-J. , Liou , C.-S. , and Pi , H.-H. , 1991 , Fault diagnosis of processing damage in injection molding via neural network approach . In Intelligent Engineering Systems Through Artificial Neural Networks , C. H. Dagli, S. R. T. Kumara, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 645 – 650 .
   Google Scholar
• YIH , Y. , LIANG , T.-P. , and MOSKOWITZ , H. , 1991 , A hybrid approach for crane scheduling problems. In Intelligent Engineering Systems Through Artificial Neural Networks , C. H. Dagli, S. R. T. Kumara, and Y. C. Shin $$eds$$ ( New York ASME ), pp. 867 – 872 .
   Google Scholar
• Yu , T. L. , 1990 , Time table scheduling using neural network algorithm . Proceedings of the IEEE International Joint Conference on Neural Networks , pp. 279 – 284 .
   Google Scholar
• ZEIDENBERG , M. , 1990 , Neural Networks in Artificial Intelligence ( New York Ellis Horwood ).
   Google Scholar
• ZURADA , J. M. , 1992 , Introduction to Artificial Neural Systems ( Minnesota West ).
   Google Scholar