Modelling of Fluidized Bed Degreasing (FBD) process by ANNs

International Journal of Surface Science and Engineering

Volumn 2, Issue 3-4, 2008, Pages 294-309

  Barletta, M ^a   Gisario, A ^a   Guarino, S ^a  

^a UNIVERSITY OF ROME TOR VERGATA   (Italy)

Author keywords

FBD; Fluidized bed degreasing; Neural network

Indexed keywords

BACKPROPAGATION ALGORITHMS; FLUIDIZED BED PROCESS; FLUIDIZED BEDS; GENETIC ALGORITHMS; NEURAL NETWORKS;

COMPARISON WITH EXPERIMENTS; DE-GREASING; EXPERIMENTAL CAMPAIGN; GENETIC ALGORITHM (GAS); MULTI LAYER PERCEPTRON; NEURAL NETWORK MODEL; OPERATIONAL PARAMETERS; PROCESS PARAMETERS;

MULTILAYER NEURAL NETWORKS;

EID: 54449096910     PISSN: 1749785X     EISSN: 17497868     Source Type: Journal    
DOI: 10.1504/IJSURFSE.2008.020500     Document Type: Article

References (18)

1. Barletta, M., Gisario, A., Guarino, S. and Tagliaferri, V. (2006) 'Fluidized bed degreasing of metal components', Journal of Machine Engineering, Vol. 6, No. 4, pp.77-97.
2. Barletta, M., Guarino, S. and Tagliaferri, V. (2002) 'Metal cleaning made easy: A fluidized bed system is a cost-effective option for degreasing processes', Metal Finishing, Vol. 102, No. 12, pp.23-28.
3. Cheng, P-J. and Lin, S-C. (2000) 'Using neural networks to predict bending angle of sheet metal formed by laser', International Journal of Machine Tools and Manufacture, Vol. 40, pp.1185-1197.
4. Cho, H-S. (2001) Neural Network Applications to Manufacturing Processes: Monitoring and Control, Korea Advanced Institute of Science and Technology (KAIST), CRC Press LLC, Seul.
5. Goldberg, D-E. (1989) Genetic Algorithm in Search, Optimization & Machine Learning, Addison-Wesley Publishing Company, Urbana - Illinois, USA.
6. Gopal, A-V. and Rao, P-V. (2003) 'Selection of optimum conditions for maximum material removal rate with surface finish and damage as constraints in SiC grinding', International Journal of Machine Tools and Manufacture, Vol. 43, pp.1237-1336.
7. Haykin, S. (1994) Neural Network: Comprehensive Foundation, Macmillan, New York.
8. Jain, R-K. and Jain, V-K. (2000) 'Optimum selection of machining conditions in abrasive flow machining using neural network', Journal of Materials Processing Technology, Vol. 108, pp.62-67.
9. Jeng, Y.J., Tzuoh, F.M. and Shyeu-Ming, L. (2000) 'Prediction of laser butt joint welding parameters using back propagation and learning vector quantization networks', Journal of Materials Processing Technology Vol. 99, pp.207-218.
10. Ko, D-C., Kim, D-H. and Kim, B-M. (1999) 'Application of artificial neural network and Taguchi method to preform design in metal forming considering workability', International Journal of Machine Tools and Manufacture, Vol. 39, pp.771-785.
11. Lu, Y-F., Song, W-D., Hong, M-H., Zheng, Y-W. and Chong, T-C. (2000) 'Laser surface cleaning and potential applications in disk drive industry', Tribology International, Vol. 33, Nos. 5-6, pp.329-335.
12. Mertens, J-A. (2000) 'Vapor degreasing with chlorinated solvents', Metal Finishing, Vol. 98, No. 6, pp.43-51.
13. Principe, J.C., Euliano, N.R. and Lefebvre, W.C. (2000) Neural and Adaptive Systems: Fundamentals through Simulations, John Wiley & Sons, Inc.
14. Reidenbach, F. (1994) Metal Handbook, 9th ed., ASM, Cleveland, OH-USA.
15. Samanta, B. (2004) 'Artificial neural networks and genetic algorithms for gear fault detection', Mechanical Systems and Signal processing Vol. 18, pp.1273-1282.
16. Scapelliti, J. (1999) 'Enclosed VD systems', Metal Finishing, Vol. 97, No. 1, pp.156-164.
17. Shibano, Y. (1997) 'Ultrasonic cleaning apparatus', Metal Finishing Vol. 95, No. 12, pp.76-76.
18. Tam, A-C., Park, H-K. and Grigoropoulos, C-P. (1998) 'Laser cleaning of surface contaminants', Applied Surface Science, Vols. 127-129, pp.721-725.