Model-based controlling of extrusion process

Abstract

Functional data analysis (FDA) is a statistical method applicable in various areas of human activities. This method allows the prediction of different process parameters based on input data that are continuously recorded during the manufacturing. The present study shows how exit section temperature in the direct extrusion of aluminum sections can be predicted enabling ram speed adjustment to obtain isothermal extrusion. A new linear regression mathematical model has been proposed for the prediction of extrudate temperature. The mathematical model has been developed using technological extrusion parameters that were measured and recorded on the real extrusion press. Simulation of the mathematical model shows that its predictions are in good accordance with the measured data on the extrusion press. In order to obtain isothermal extrusion, adequate ram speed curve was calculated from the proposed mathematical model.