Artificial Neural Network to the Control of the Parameters of the Heat Treatment Process of Casting

Journal title

Archives of Foundry Engineering




No 1

Publication authors


Heat treatment ; Moving heat source ; Artificial neural network ; Numerical modelling ; System of the control of the heatingprocess

Divisions of PAS

Nauki Techniczne


Archives of Foundry Engineering continues the publishing activity started by Foundry Commission of the Polish Academy of Sciences (PAN) in Katowice in 1978. The initiator of it was the first Chairman Professor Dr Eng. Wacław Sakwa – Corresponding Member of PAN, Honorary Doctor of Czestochowa University of Technology and Silesian University of Technology. This periodical first name was „Solidification of Metals and Alloys” , and made possible to publish the results of works achieved in the field of the Basic Problems Research Cooperation. The subject of publications was related to the title of the periodical and concerned widely understand problems of metals and alloys crystallization in a casting mold. In 1978-2000 the 44 issues have been published. Since 2001 the Foundry Commission has had patronage of the annually published “Archives of Foundry” and since 2007 quarterly published “Archives of Foundry Engineering”. Thematic scope includes scientific issues of foundry industry:

  • Theoretical Aspects of Casting Processes,
  • Innovative Foundry Technologies and Materials,
  • Foundry Processes Computer Aiding,
  • Mechanization, Automation and Robotics in Foundry,
  • Transport Systems in Foundry,
  • Castings Quality Management,
  • Environmental Protection.


In the paper the use of the artificial neural network to the control of the work of heat treating equipment for the long axisymmetric steel

elements with variable diameters is presented. It is assumed that the velocity of the heat source is modified in the process and is in real

time updated according to the current diameter. The measurement of the diameter is performed at a constant distance from the heat source

(∆z = 0). The main task of the model is control the assumed values of temperature at constant parameters of the heat source such as radius

and power. Therefore the parameter of the process controlled by the artificial neural network is the velocity of the heat source. The input

data of the network are the values of temperature and the radius of the heated element. The learning, testing and validation sets were

determined by using the equation of steady heat transfer process with a convective term. To verify the possibilities of the presented

algorithm, based on the solve of the unsteady heat conduction with finite element method, a numerical simulation is performed. The

calculations confirm the effectiveness of use of the presented solution, in order to obtain for example the constant depth of the heat

affected zone for the geometrically variable hardened axisymmetric objects.


The Katowice Branch of the Polish Academy of Sciences


2015[2015.01.01 AD - 2015.12.31 AD]


Artykuły / Articles


ISSN 2299-2944