Electro-discharge machining (EDM) is increasingly being used in many industries for producing molds and dies, and machining complex shapes with material such as steel, cemented carbide, and engineering ceramics. The stochastic nature of EDM process has frustrated number of attempts to model it physically. Artificial neural networks (ANNs), as one of the most attractive branches in Artificial Intelligence (AI), has the potentiality to handle problems such as prediction of design and manufacturing cost, material removal rate (MRR), diagnosis, modeling, and adaptive control in a complex design and manufacturing systems. This paper uses Back Propagation Neural Network (BP) and Radial Basis Function (RBF) approach for prediction of material removal rate and surface roughness and presents the results of the experimental investigation. Charmilles Technology (EDM-ROBOFORM200) in he mechanical engineering department is used for machining parts. The networks have four inputs of current (I), voltage (V), Period of pulse on (Ton) and period of pulse off (Toff) as the input processes variables. Two outputs results of material removal rate (MRR) and surface roughness (Ra) as performance characteristics. In order to train the network, and capabilities of the models in predicting material removal rate and surface roughness, experimental data are employed. Then the output of MRR and Ra obtained from neural net compare with experimental results, and amount of relative error is calculated.
This paper addresses the concept of the Expert system approach for CASD/CAM integration and optimization of product design and manufacturing in computer base concurrent engineering environment. The Expert system links with design and manufacturing databases. The design specification is acquired through a feature based approach. The Expert system links with material, tools, CNC machine center data and databases. For each design feature, the expert system provides information needed for design and manufacturing optimization. The expert system can be used as an advisory system for designers and manufacturing engineers using STEP (standard for exchange of product data) AP224 standard. and also for new CNC machine center operators. A designer uses proengineers software and feature base library and design a part. Design data stored in data base according to international standard STEP format. All suppliers can used the latest design data through computer network system and STEP design data. The result of table 1 shows that the expert system estimates correctly machining cycle time and cost and penetration rate. In practical, estimation of machining time and cost, feeds and all other parameters are difficult to obtain. In contrast the expert system can provide this estimation usually in less than 20 seconds.
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