engleski

Functional Data Analyses in Control of Extrusion Process

Functional data analysis (FDA) is a relatively new method which has application in various areas of human activities. Recently, it has been used in analysis of manufacturing processes which are numerically controlled by PLC devices. Typical such processes in the aluminum industry are DC casting facilities, rolling mills and extrusion presses. This method allows the prediction of different variables based on input data that are recorded during each of these processes. The present study shows how some of the important extrusion parameters, such as extrusion force, section temperature and others can be predicted. A new linear regression mathematical model has been proposed for the prediction of these parameters. Regression coefficients of the model are in the form of time dependent functions that have been determined through the use of FDA methodology. The mathematical model has been developed using data for technological extrusion parameters that were measured and recorded on a real extrusion press. Simulation of the mathematical model shows that its predictions are in good in accordance with the measured data on the extrusion press.

Functional data analysis; Extrusion; Mathematical modelling

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