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Journal of Engineering and Applied Sciences

ISSN: Online 1818-7803
ISSN: Print 1816-949x
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Prediction and Optimization of Machining Parameters for Cutting Al6061/MoS2 MMC Material by WEDM Process

M. Geeta Rani, Ch.V.S. Parameswara Rao and K. Rama Kotaiah
Page: 8483-8488 | Received 21 Sep 2022, Published online: 21 Sep 2022

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Abstract

Wire cut Electric Discharge Machining (WEDM) is a vital technology which is required for high speed cutting and high precision machining to enhance productivity and accuracy for manufacturing of press tools, moulds, prototype parts and complicated contours etc. The machining system involves many input parameters effecting output. The main objective of this research is to determine the optimum values of machining parameters for attaining economical and competent performance for machining Al6061/MoS2 Metal Matrix Composite (MMC). The MMC material was made by stir casting process and the specimen were prepared for machining as well as testing. The cutting operations were carried out on WEDM by varying the machining current on work pieces of thickness ranging from 5-80 mm. The surface roughness value was measured using Talysurf. The Material Removal Rate (MRR) was computed by measuring cutting width using profile projector. The optimal current value at which the machining is stable with high cutting speed is identified. Mathematical correlations are developed to determine the cutting parameters, the MRR and surface roughness by using Origin software. The same parameters were analyzed using RSM technique and the results were compared. The correlations developed are useful for evaluating the machining parameters for different machining situations arising out of customer requirements and machining time calculation in turn cost of machining.


How to cite this article:

M. Geeta Rani, Ch.V.S. Parameswara Rao and K. Rama Kotaiah. Prediction and Optimization of Machining Parameters for Cutting Al6061/MoS2 MMC Material by WEDM Process.
DOI: https://doi.org/10.36478/jeasci.2018.8483.8488
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.8483.8488