Integrated feed-forward artificial neural networks system for machines tools selection

The choice of the machine tools is one of the considerations of manufacturing companies which depend primarily on machining process, by deciding how a finished product will be manufactured. The activity of tools choice is established in geometry of machining features, but it also has a direct impact on workability and execution of machine-tool. We propose in this paper an integration module of the automatic choice of machine tools in the environment of systems CAD/CAM, which consisted in the two neuronal systems NN1 and NN2; NN1 allows the automatic machining machines choice. NN2 makes it possible to choose cutting tools for machining features. In this work, we have worked two complementary parts for the integration of the automatic choice of machine tools. Firstly we developed a neuronal system for selection of machine tools classes. Secondly, we have created an interface of neuronal system integration which exploits machining features geometrical data to be carried out by Visual Basic programming.