Neural Network Approach to Cutting Tools Selection

Abstract

Cutting tools selection is a key issue in today's research of computer aided process planning (CAPP). Traditionally, this task is carried out by process planners and knowledge base systems. Recently, process planners have started using newer artificial intelligent techniques, such as neural networks, fuzzy logic, intelligent agents, etc. to model cutting tools. In this study, the problem of cutting tools selection for milling and drilling operations is investigated. A neural network model is proposed to select the needed cutting tools and their geometry based feature type and machining operation. Feature type, feature condition, dimension ratio, feature taper and machining operation are presented to the network for each feature as input parameters. The network selects the required cutting tool. The advantage and effectiveness of the proposed model are verified through a several types of machining features