Florica Mioara ŞERBAN, Ciprian CRISTEA, Emilia SABĂU, Vasile CECLAN, Glad CONŢIU


Thickness is one of the major quality characteristics of drawn parts. In this paper a fuzzy expert system is designed to predict the thickness along cup wall in deep drawing of cylindrical cups. After using the finite element results for training and testing, the developed fuzzy system was applied to new data for prediction of thickness distribution in deep drawing of cylindrical cups. The prediction results were compared with finite element simulation. The results show that de fuzzy expert system can accurately predict the thickness variation of drawn cups.

Full Text:



Banabic, D., Dörr, I.R. Deformabilitatea tablelor metalice subţiri. Metoda curbelor limită de deformare, Editura O.I.D.I.C.M., Bucureşti, 1992.

Darlington K., The essence of expert system, Prentice Hall, Essex, 2000.

Fasanghari, M., Montazer, G. A., Design and implementation of fuzzy expert system for Tehran Stock Exchange portfolio recommendation, Expert Systems with Applications, vol. 37, no. 9, pp. 6138–6147, 2010.

Haji, A., Assadi, M., Fuzzy expert systems and challenge of new product pricing, Computers & Industrial Engineering, vol. 56, issue 2, pp. 616–630, 2009.

Klir G. J., Yuan, B., Fuzzy sets and Fuzzy logic: theory and applications, Prentice-Hall, New-York, 1995.

Lin, C., Chen, C., New Product Go/No-Go Evaluation at the Front End: A Fuzzy Linguistic Approach, IEEE Transactions on Engineering Management, 51(2), pp. 197–207, 2004.

Machacha, L. L., Bhattacharya, P., A fuzzy-logic-based approach to project selection, IEEE Transactions on Engineering Management, 47(1), pp. 65–73, 2000.

McCarthy, J., Some expert system need common sense, in Pagels H. R. (Ed.), Computer culture: The scientific, intellectual and social impact of the computer, New York Academy of Science, New York, 1984.

Ngai, E. W. T., Wat F.K.T., Design and development of a fuzzy expert system for hotel selection, Omega, 31, pp. 275–286, 2003.

Padmanabhan R., Oliveira M.C., Alves J.L., Menezes L.F., Influence of process parameters on the deep drawing of stainless steel, Finite Elements in Analysis and Design, vol. 43, issue 14, pp. 1062 – 1067, 2007.

Piltan M., Mehmanchi E., Ghaderi S.F., Proposing a decision-making model using analytical hierarchy process and fuzzy expert system for prioritizing industries in installation of combined heat and power systems, Expert Systems with Applications 39(1), pp. 1124–1133, 2012.

Raju S., Ganesan G., Karthikeyan R., Influence of variables in deep drawing of AA 6061 sheet, Transactions of Nonferrous Metals Society of China, 20(10), pp. 1856-1862, 2010.

Rosinger Şt., Procese şi scule de presare la rece. Culegere de date pentru proiectare, Editura Facla, Timişoara, 1987.

Ross, T. J., Fuzzy logic with engineering applications, John Wiley & Sons, Chicester, 2004.

Singh S. K., Gupta A. K., Application of support vector regression in predicting thickness strains in hydro-mechanical deep drawing and comparison with ANN and FEM, CIRP Journal of Manufacturing Science and Technology, vol. 3, issue 1, pp. 66–72, 2010.

Smith D.A., Die Design Handbook, Society of Manufacturing Engineers, Dearborn, 1990.

Suchy I., Handbook of Die Design (2nd ed.), McGraw-Hill, New York, 2006.

Tăpălagă I., ş.a., Tehnologia presării la rece, vol. I, Litografia Institutului Politehnic, Cluj-Napoca, 1985.

Zadeh L. A., Fuzzy sets, Information and Control, 8(3), pp. 338–353, 1965.

Zimmermann H. J., Fuzzy set theory – and its applications (3rd ed.), Kluwer Academic Publishers, Boston, 1996.

*** eta/DYNAFORM. User’s Manual (Electronic documentation, – release 5.6.1). Engineering Technology Associates, 2008.


  • There are currently no refbacks.