Dynamic model of the machining process on the basis of neural networks: From simulation to real time application

Abstract

Nowadays, thc modeling of complex manufacturing tasks is a key issue. In this work, as a case study is selected the application of a dynamic model to predict cutting force in machining processes. A model created using Artificial Neural Networks (ANN), able to predict thc process output is introduced in order to deal with the characteristics of such an ill-defined process. This model describes the dynamic response of the output before changes in the process input command (feed rate) and process parameters (depth of cut). Experimental tests are made in a professional machining centre, with different cutting conditions, on real time data. Thc model provides sufficiently accurate prediction of cutting force, since the process-dependent specific dynamic properties are adequately rcflected. © Springer-Verlag 2002.