Al-based classification methodologies for the modelling of machine tool thermal error

Abstract

Machine tool accuracy in a production environment is quite different from that under ideal laboratory conditions as it is subject to a variety of operating states. In addition to these variations, there is also the change in accuracy brought about by the rise in temperature of the machine components. Modelling of the machine tool thermal error is therefore a complex task necessitating the classification of the error into groups before they can be mapped with the temperature. In this paper, we attempt to apply and analyse three different classification methodologies so as to arrive at the most effective solution.