Radomir Slavković

An application of learning machine methods in prediction of wear rate of wear resistant casting parts

In this paper, a method of floating ball wear rate identification, using two machine-learning techniques Support Vector Machine (SVM) and Improved Support Vector Machine (ISVM) are proposed. Both models are used to relate the wear rate and technological parameters of the wear resistant drip moulding using different kernel functions. The models for determining the wear rate of white iron casting with low chromium content (flotation balls), was trained and tested by using the existing exploitation data from the Bor Flotation Plant, Serbia. In order to select the best model parameters the statistical indicators for both models are presented. Results show that the ERBF (SVM) and ERBF+POLY (ISVM) achieved the best classification accuracy compare to other kernels used: the absolute mean error of ERB (SVM) is 5.85%, while the error of ERBF+POLY (ISVM) is 6.67%. The tuned ISVM model with mixture of kernels is able to accurately predict the wear rate and can be used to define the optimum chromium content in liquid metal alloys for the casting of flotation balls.

Optimization of the Gating System for Sand Casting Using Genetic Algorithm

The paper presents a methodology of optimization of the gating system for sand casting using the genetic algorithm. Software package for computer-aided design/computer-aided manufacturing (CAD/CAM) was used as the support to the design and verification of the optimized gating system. The geometry of the gating system of sand casting in excavator tooth holder was the subject of optimization. The objective was to maximize filling rate given the constraints posed by both the ingate module and Reynolds number. Mold filling time has been presented as a function of the ingate cross section and casting height. Given the conditions above, as the result of the optimization, a complete geometry of the gating system has been defined. Numerical simulation (software MAGMA5) has been used to verify the validity of the optimized geometry of the gating system.