Experimental investigation on aluminium composite surface machined by electrical discharge machining process using response surface methodology / R. Rajesh and M. Dev Anand
industry. Nowadays there is a critical need for cost-effective machining processes for this material. Not much work has been reported for machining of Aluminum based composite with Electrical Discharge Machining (EDM) process. In this work, an attempt has been made to model the machinability evaluat...
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| Format: | Article |
| Language: | English |
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Faculty of Mechanical Engineering
2013
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| Online Access: | http://ir.uitm.edu.my/id/eprint/17615/ http://ir.uitm.edu.my/id/eprint/17615/4/AJ_R.%20RAJESH%20JME%2013.pdf |
| Summary: | industry. Nowadays there is a critical need for cost-effective machining processes for this material. Not much work has been reported for machining of Aluminum based composite with Electrical Discharge Machining (EDM) process. In this work, an attempt has been made to model the machinability evaluation through the Response Surface Methodology (RSM) while machining of Al-10% SiCp Metal Matrix Composite (MMC) was manufactured through stir casting method. The experimental results obtained aims at the selection of optimal machining conditions for EDM of Aluminum based MMC. The work piece material has been cleverly considered as control factor along with the combined effect of six controllable input variables and its effect on the surface roughness has been investigated with the minimum number of experiments. Analysis of variance is performed to get contribution of each parameter on the performance characteristics and it was observed that the discharge current is the significant process parameter that affects the EDM robustness. The contour plots were generated to study the effect of process parameters as well as their interactions. The experimental analysis for the optimal setting shows that there is considerable improvement in the process. The application of this technique converts the response variable to a single response process parameters which are optimized using Box Behnken based approach RSM and thus simplifies the optimization procedure. Result of confirmation experiments shows that the established mathematical models can predict the output response which satisfy the real requirement in practice. |
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