Interactive multi-objective artificial neural network approach for machine setup optimization

Journal of Intelligent Manufacturing

Volumn 11, Issue 1, 2000, Pages 41-50

  Malakooti, Behnam ^a   Raman, Vishnu ^a  

^a Case Western Reserve University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; COST EFFECTIVENESS; CUTTING; DECISION MAKING; MACHINE TOOLS; MACHINING; OPTIMIZATION; PRODUCTIVITY; SCHEDULING; SERVICE LIFE; SURFACE ROUGHNESS;

BACKPROPAGATION NEURAL NETWORK; INTELLIGENT MULTIOBJECTIVE OPTIMIZATION; INTERACTIVE MULTIOBJECTIVE ARTIFICIAL NEURAL NETWORK; MACHINE SETUP OPTIMIZATION;

NEURAL NETWORKS;

EID: 0033878853     PISSN: 09565515     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1008999907768     Document Type: Article

References (23)

1. Armarego, E. J. A. and Brown, R. H. (1969) The machining of metals, Prentice-Hall Inc, Englewood Cliffs, NJ.
2. Bhattacharya, A., Faria-Gonzalez, R. and Ham, I. (1970) Regression analysis for predicting surface finish and its application in the determination of optimum machining conditions. Journal of Engineering for Industry, 92, 711-714.
3. Fang, X. D. and Jawahir, S. I. (1994) Predicting total machining performance in finish turning using integrated fuzzy-set models of the machinability parameters. International Journal of Production Research, 32(4).
4. Grossberg, S. (1976) Adaptive pattern classification and universal recording I: parallel development and coding of neural feature detectors. Biological Cybernetics, 23, 121-134.
5. Grossberg, S. (1987) Competitive learning: from interactive activation to adaptive resonance. Cognitive Science, 11, 23-63.
6. Hati, S. and Rao, S. S. (1977) Determination of optimum machining conditions-deterministic and probabilistic approaches, Journal of Engineering for Industry, 99, 354-359.
7. Kohonen, T. (1984) Self-organization and Associative Memory, Springer-Verlag, Berlin.
8. Kohonen, T. (1988) An introduction to Neural Computing. Neural Networks, 1, 3-16.
9. Li, S. and Elbestawi, M. A. (1996) Tool condition monitoring in machining by fuzzy neural networks. Transactions of ASME, Journal of Dynamic Systems, 118(4).
10. Malakooti, B., Wang, J. and Tandler, E. (1990) A sensor-based accelerated approach for multiple-attribute machinability and tool life evaluation. International Journal of Production Research, 28(12), 2373-2392.
11. Malakooti, B. (1991) An interactive on-line multi-objective optimization approach for metal cutting turning operation. International Journal of Production Research, 29(3), 575.
12. Malakooti, B. and Zhou, Y. (1994) Feedforward artificial neural network for solving discrete multiple criteria decision making problem. Management Science, 40, 1542-1561.
13. Malakooti, B. and Yang, Z. (1995) A variable unsupervised learning clustering neural network approach with application to machine-part group formation. International Journal of Production Research, 33(9), 2395-2413.
14. Malakooti, B., Zhou, Y. and Tandler, E. C. (1995) In-process regressions and adaptive neural networks for monitoring and supervising machining operations. Journal of Intelligent Manufacturing, 6, 53-66.
15. Malakooti, B. and Zhou, Y. (1998) Approximating polynomial functions by feedforward artificial neural networks: capacity, analysis, and design. Applied Mathematics and Computation, 90, 27-52.
16. Malakooti, B. and Subramanian, S. (1999) Generalized polynomial decomposable multiple attribute utility functions for ranking and rating of alternatives. Applied Mathematics and Computation, 106, 69-102.
17. Matsushima, K. and Sata, T. (1980) Development of intelligent machine tool. Journal of faculty English, University of Tokyo, 35.
18. Mesquita, R., Krasteva, E. and Doytchinov, S. (1995) Computer-Aided selection of optimum machining parameters in multipass turning. International Journal of Advanced Manufacturing, 10(1).
19. Pao, Y. H. (1989) Adaptive Pattern Recognition and Neural Networks, Addison-Wesley, Reading, MA.
20. Rangawala, S. and Dornfeld, D. (1989) Learning and optimization of machining operations using computing abilities of neural networks. IEEE Transactions on System, Man and Cybernetics, 19, 299-314.
21. Rumelhart, D. E. and Zipser, D. (1985) Feature discovery by competitive learning. Cognitive Science, 9, 75-112.
22. Rumelhart, D. E., Hinton, G. and Williams, R. (1986) Learning internal representations by back-propagating errors. Nature, 323, 533-536.
23. Wang, J. and Malakooti, B. (1992) A feedforward neural network for multiple criteria decision making. Computers and Operations Research, 19(2), 151-167.