Optimal Reheating Condition of Semi-solid Material in Semi-solid Forging by Neural Network

  • Park, Jae-Chan (School of mechanical engineering, Pusan National University) ;
  • Kim, Young-Ho (School of mechanical engineering, Pusan National University) ;
  • Park, Joon-Hong (Research of institute of Mechanical Technology, Pusan National University)
  • Published : 2003.03.01

Abstract

As semi-solid forging (SSF) is compared with conventional casting such as gravity die-casting and squeeze casting, the product without inner defects can be obtained from semi-solid forming and globular microstructure as well. Generally, SSF consists of reheating, forging, and ejecting processes. In the reheating process, the materials are heated up to the temperature between the solidus and liquidus line at which the materials exists in the form of liquid-solid mixture. The process variables such as reheating time, reheating temperature, reheating holding time, and induction heating power has large effect on the quality of the reheated billets. It is difficult to consider all the variables at the same time for predicting the quality. In this paper, Taguchi method, regression analysis and neural network were applied to analyze the relationship between processing conditions and solid fraction. A356 alloy was used for the present study, and the learning data were extracted from the reheating experiments. Results by neural network were in good agreement with those by experiment. Polynominal regression analysis was formulated using the test data from neural network. Optimum processing condition was calculated to minimize the grain size and solid fraction standard deviation or to maximize the specimen temperature average. Discussion is given about reheating process of row material and results are presented with regard to accurate process variables fur proper solid fraction, specimen temperature and grain size.

References

  1. Spencer, D. B., Meharabian, R. and Flemings, M. C., 'Rheological Behavior of Sn-15%Pb in the Crystallization Range,' Met. Trans., Vol. 3, PP. 1925-1932, 1972 https://doi.org/10.1007/BF02642580
  2. Kenny, M. P., Courtois, J. A., Evans, R. D., Farrior, G. M., Kyonka, C. R, Couch, A. A., Young, K. R, 'Semisolid Metal Casting and Forming,' Metal Handbook 9th Ed., Vol. 15, PP. 327-338, 1988
  3. Hirt, G., Cremer, R., Winkelmann, A., Witulski, T. and Zillgen, M., 'SSM-Forming of Usually Wrought Aluminium Alloys,' Proc. 3rd. Int. Conf. on Processing of Semi-Solid Alloys and Composites, University of Tokyo. PP. 107-116, 1994
  4. Kenneth P. Young and Rudolf Fitze, 'Semi-Solid Metal Cast Aluminium Automotive Components,'The 3rd Int. Conf. on Semi-Solid Processing of Alloys and Composites, PP. 155-189, 1994
  5. Cremer, R., Winkelmann, A. and Hirt, G., 'Sensor controlled induction heating of aluminium alloys for semi solid forming,' The 4th Int. Conf. on Semi-Solid Processing of Alloys and Composites, University of Sheffed, PP. 159-164, 1996
  6. Jung, Hong-Kyu and Kang, Chung-Gil, 'A Study on Induction Heating Process of A1-6%Si-3%Cu-0.3%Mg Alloy for Thixoforming,' Journal of the Korean Foundrymen's Society, Vol. 19, No. 3, PP. 225-235, 1999
  7. Ohnaka, I., 'Introduction to Heat and Solidification Analysis by Computer,' Marusen Press, PP. 196-199, 1985
  8. Flemings, M. C., 'Solidification Processing,'McGraw-Hill Book Company, New York, PP. 31-36, 1974