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.