Architecture and training algorithm of feed forward artificial neural network to predict material removal rate of electrical discharge machining process

This paper presents a model of a feed forward arti cial neural network to predict the material removal rate of an electrical discharge machine process. A new modi ed architecture and training algorithm is proposed by segmenting the roughing and fi nishing machining parameters of the process. The segmentation is performed in order to obtain a lower di erence between the actual and predicted material removal rates. Through comparative analysis and results obtained between the two architectures, it is found that the new modi ed feed forward arti cial neural network produces lower error between the experimental and predicted material removal rates, thus, improving the accuracy of the prediction model.

[1]  Yi Wang,et al.  A hybrid intelligent method for modelling the EDM process , 2003 .

[2]  K. V. Prema,et al.  Generalization Capability of Artificial Neural Network Incorporated with Pruning Method , 2011, ADCONS.

[3]  Yang Dayong,et al.  The study of high efficiency and intelligent optimization system in EDM sinking process , 2004 .

[4]  M. S. Shunmugam,et al.  Multi-objective optimization of wire-electro discharge machining process by Non-Dominated Sorting Genetic Algorithm , 2005 .

[5]  Y. S. Tarng,et al.  Optimisation of the electrical discharge machining process using a GA-based neural network , 2003 .

[6]  C. L. Lin,et al.  Optimisation of the EDM Process Based on the Orthogonal Array with Fuzzy Logic and Grey Relational Analysis Method , .

[7]  Azli Yahya,et al.  Determination of material removal rate of an electro-discharge machine using dimensional analysis , 2004 .

[8]  C. L. Lin,et al.  The use of grey-fuzzy logic for the optimization of the manufacturing process , 2005 .

[9]  Pei-Jen Wang,et al.  Comparisons of neural network models on material removal rate in electrical discharge machining , 2001 .

[10]  Azli Yahya,et al.  Predicting Material Removal Rate of Electrical Discharge Machining (EDM) using Artificial Neural Network for High Igap current , 2011, International Conference on Electrical, Control and Computer Engineering 2011 (InECCE).

[11]  M. Ghoreishi,et al.  Neural-network-based modeling and optimization of the electro-discharge machining process , 2008 .

[12]  Surjya K. Pal,et al.  Modeling of electrical discharge machining process using back propagation neural network and multi-objective optimization using non-dominating sorting genetic algorithm-II , 2007 .

[13]  Gary F. Benedict,et al.  Nontraditional Manufacturing Processes , 1987 .

[14]  Kuldeep Ojha,et al.  MRR Improvement in Sinking Electrical Discharge Machining: A Review , 2010 .