Forward and reverse mappings in green sand mould system using neural networks

Applied Soft Computing Journal

Volumn 8, Issue 1, 2008, Pages 239-260

  Parappagoudar, Mahesh B ^a   Pratihar, D K ^a   Datta, G L ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY   (India)

Author keywords

BPNN; Forward and reverse mappings; GA NN; Green sand mould system

Indexed keywords

COMPRESSIVE STRENGTH; GRAIN SIZE AND SHAPE; MECHANICAL PERMEABILITY; METAL CASTINGS; NEURAL NETWORKS;

BPNN; FORWARD AND REVERSE MAPPINGS; GREEN SAND MOULD SYSTEM;

MAPPING;

EID: 34548489637     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2007.01.005     Document Type: Article

References (21)

1. Babu N.N., Ohdar R.K., and Pushp P.T. Evaluation of green compressive strength of clay bonded moulding sand mix: neural network and neuro-fuzzy based approaches. Int. J. Cast Met. Res. 19 (2006) 110-115
2. In: Brown J.R. (Ed). Foseco Non-Ferrous Foundry Man's Handbook. 11th ed. (1999), A Division of Reed Educational and Professional Publishing Limited, Butterworth-Heinemann, Woburn
3. Chang Y., and Hocheng H. The flowability of moulding sand. J. Mater. Process. Technol. 113 (2001) 238-244
4. Dai H., and Macbeth C. Effects of learning parameters on learning procedure and performance of a BPNN. Neural Networks 10 (1997) 1505-1521
5. Dhindaw B.K., and Chakraborty M. Study and control of properties and behaviour of different sand systems by application of statistical design of experiments. Proceedings of the 41st International Foundry Congress. Belgique (1974) 9-14
6. Dietert H.W., Brewster F.S., and Graham A.L. A straight line approach to sand control. AFS Trans. 74 (1966) 101-111
7. Heine R.W., Loper C.R., and Rosenthal P.C. Principles of Metal Casting. 2nd ed. (1976), Tata McGraw-Hill publishing Company Limited, New Delhi
8. Jain P.L. Principles of Foundry Technology. 4th ed. (2003), Tata McGraw-Hill Publishing Company Limited, New Delhi
9. Karunakar D.B., and Datta G.L. Modelling of green sand mould parameters using artificial neural networks. Ind. Foundry J. 49 (2003) 27-36
10. Kosko B. Neural Networks and Fuzzy Systems. 1st ed. (2002), Printice-Hall of India Private Limited, New Delhi
11. Montgomery D.C. Design and Analysis of Experiments. 5th ed. (2001), John Wiley & Sons, New York
12. M.B. Parappagoudar, D.K. Pratihar, G.L. Datta, Linear and non-linear statistical modeling of green sand mould system, Int. J. Cast Met. Res., in press.
13. Parappagoudar M.B., and Bhat R.P. Developing mathematical models to improve quality characteristics of sand moulds. Proceedings of the National Conference on World Class Manufacturing. Amrita Institute of Technology, Coimbatore (2002) 199-204
14. Parappagoudar M.B., Pratihar D.K., and Datta G.L. Green sand mould system modelling through design of experiments. Ind. Foundry J. 51 (2005) 40-51
15. M.B. Parappagoudar, D.K. Pratihar, G.L. Datta, Non-linear modeling using central composite design to predict green sand mould properties, Proceedings of the IMechE Part-B J. Eng. Manuf., in press.
16. Rao M.A., and Srinivas J. Neural Networks Algorithms and Applications. 1st ed. (2004), Narosa Publishing House, New Delhi
17. Rao P.N. Manufacturing Technology. 1st ed. (1994), Tata McGraw-Hill Publishing Company Limited, New Delhi
18. Rose D.C., Vingas G.J., and Taylor L.E. Properties of base sands-bentonite bonding. AFS Trans. 72 (1964) 36-47
19. Srinagesh K., Seshadri M., and Ramchandran A. On the compaction of bonded grains. AFS Trans. 74 (1966) 27-36
20. Wong M.L.D., and Nandi A.K. Automatic digital modulation recognition using artificial neural network and genetic algorithm. Signal Process. 84 (2004) 351-365
21. Wu C.F.J., and Hamada M. Experiments Planning, Analysis, and Parameter Design Optimization. 1st ed. (2000), John Wiley & Sons, New York