Neural network modelling and parameters optimization of increased explosive electrical discharge grinding (IEEDG) process for large area polycrystalline diamond

Neural network–based modeling to predict residual stresses during electric discharge machining of Al/SiC metal matrix composites

“…The results were analyzed using genetic algorithm developed using neural network for optimization of the results. 23 In another study, Taguchi's L27 orthogonal array was used to present feed forward neural network based on BP along with a regression model to predict the surface roughness in abrasive jet machining process. 24 The ANNs were applied successfully during machining and can accurately predict the responses during EDM.…”

A study on micro-hole machining of polycrystalline diamond by micro-electrical discharge machining

“…The electrical discharge grinding process offers a lower cost alternative with inherent higher accuracy for surface shaping of PCD blanks. Cao and Zhang (2004) developed a neural network model for an increased explosive electrical discharge grinding process and in their study the machining performance was improved with the material removal rate increased to 9.75 mm 3 /min and the depth of diamond tungsten carbide (WC) interface reduced to 0.03 mm. Electrical discharge milling proposed by Liu et al (1997) is able to effectively machine a large surface area on a PCD, where a DC source is employed and a water-based emulsion is used as the machining fluid.…”

Genetic algorithm for optimization of welding variables for height to width ratio and application of ANN for prediction of bead geometry for TIG welding process

“…Recent developments in the evolution of artificial neural networks have been found to be useful in solving many engineering problems. In different fields of engineering, back-propagation neural network has proved to be one of the best algorithms for predictive type of work [7][8][9][10][11][12][13][14][15][16]. Genetic algorithms are attracting the attention of many researchers when it comes to optimization of process parameters.…”