Influence of moulding sands grain size on the effectiveness of quality control systems
Journal Title: Archiwum Odlewnictwa - Year 2011, Vol 11, Issue 2
Abstract
One of the modern methods of the production optimisation are artificial neural networks. Neural networks owe their popularity to the fact that they constitute convenient tools, which can be applied in an extremely broad research scope. This is caused by their ability to represent complex functions. Their non-linearity should be specially emphasised. Neural networks are gaining broader and broader application in the foundry industry, among others for controlling melting processes in cupolas and in arc furnaces, for designing castings and supply systems, for controlling moulding sand processing, for predicting properties of cast alloys or selecting parameters of pressure castings. An attempt to apply neural networks for controlling the quality of bentonite moulding sands is presented in this paper. This is the assessment method of sands suitability by means of detecting correlations between their individual parameters. The presented investigations were obtained by using the Statistica 9.0 program. The aim of the investigations was to select the neural network suitable for prediction the moulding sand moisture on the basis of the determined sand properties such as: permeability, compactibility, friability and compressive strength in dependence on the matrix grain size.
Authors and Affiliations
J. Jakubski, St. M. Dobosz, K. Major-Gabryś
Keywords
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