Title: Prediction of surface roughness during wire electrical discharge machining of SiCp/6061 Al metal matrix composite
Authors: Pragya Shandilya; P.K. Jain; N.K. Jain
Addresses: Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee, 247 667 Uttarakhand, India ' Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee, 247 667 Uttarakhand, India ' Department of Mechanical Engineering, Indian Institute of Technology, Indore, 452 017 Madhya Pradesh, India
Abstract: In this work, response surface methodology (RSM) and artificial neural network (ANN) techniques were used for predicting the surface roughness during wire electrical discharge machining (WEDM) of SiCp/6061 Al metal matrix composite. Box–Behnken design approach has been used and totally 29 experiments were carried out using four process input variables, i.e. servo voltage, pulse-on time, pulse-off time and wire feed rate. The mathematical relationship between WEDM input process parameters and surface roughness was established to determine the value of surface roughness mathematically. The RSM predicted values and ANN predicted values of surface roughness were compared with the experimental values and their closeness with the experimental values was determined. Good agreement was observed between the predicted model results and experimental results. Finally, the ANN model and RSM model for surface roughness were compared with each other.
Keywords: WEDM; wire EDM; electrical discharge machining; MMC; metal matrix composites; ANNs; artificial neural networks; RSM; response surface methodology; surface roughness; surface quality; electro-discharge machining; silicon carbide; aluminium; servo voltage; pulse-on time; pulse-off time; wire feed rate.
International Journal of Industrial and Systems Engineering, 2012 Vol.12 No.3, pp.301 - 315
Available online: 03 Oct 2012 *Full-text access for editors Access for subscribers Purchase this article Comment on this article