Andere Kunden interessierten sich auch für
![Optimization of Wire Electrical Discharge Machining]( "Optimization of Wire Electrical Discharge Machining")
Optimization of Wire Electrical Discharge Machining36,99 €![Optimization of Wire-EDM Process Parameters on TI-6AL-4V]( "Optimization of Wire-EDM Process Parameters on TI-6AL-4V")
Optimization of Wire-EDM Process Parameters on TI-6AL-4V26,99 €![Optimization of process parameters in Wire-EDM]( "Optimization of process parameters in Wire-EDM")
Optimization of process parameters in Wire-EDM26,99 €![Performance Investigation of Wire EDM Process Parameters using MOGA]( "Performance Investigation of Wire EDM Process Parameters using MOGA")
Performance Investigation of Wire EDM Process Parameters using MOGA36,99 €![Analysis and Optimization of Die Corner Accuracy in Wire Cut-EDM]( "Analysis and Optimization of Die Corner Accuracy in Wire Cut-EDM")
Analysis and Optimization of Die Corner Accuracy in Wire Cut-EDM42,99 €![OPTIMIZATION OF WIRE DRAWING PROCESS PARAMETERS]( "OPTIMIZATION OF WIRE DRAWING PROCESS PARAMETERS")
OPTIMIZATION OF WIRE DRAWING PROCESS PARAMETERS36,99 €![Unconventional machining process using advanced optimization technique]( "Unconventional machining process using advanced optimization technique")
Unconventional machining process using advanced optimization technique44,99 €
The present work is devoted to the development of ANN models for the analysis of the WEDM process applied to an actual industrial surface quality of components of mould and dies. Four layered structure (including two hidden layers, input and output layer) with back propagation for ANN model is selected and two fold cross-over data approach has been used to develop two different sets of models (S1 & S2) for each experimental set of material rods. Extensive computational results (predicted output values) have been obtained by using training, validation and testing programmed in "MATLAB R2010a". Prediction error statistics and correlations coefficient testing carried out between experimental and predicted outputs Ra as well as MRR to evaluate the best modeling result. The best among the proposed ANN models has been used to optimize the process parameter (Ra) with MRR by the effort of best input parametric combination.