Abstract
Grinding with pearl mill capable of solid particles grinding in emulsions or greases from granulation of approximately 30–1 μm was studied on the basis of statistically planned experiments. The fractional factorial design for five factors was implemented. The data were used for modelling to develop back-propagation neural network and incomplete higher order polynoms. The obtained models were used for determination of the correlations among selected variables and for prediction of optimal values. Energy consumption and time were of our special interest and were directly dependent on the granualisation of the particles, i.e. smaller particles demand more energy and longer milling time. On the basis of the developed models and selected size of particles, the energy consumption and the time of milling could be predicted. The problems inherent in the modelling with mentioned models were discussed in detail.
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