Back to Search Start Over

PREDICTION OF SURFACE ROUGHNESS IN WIRE CUT ELECTRIC DISCHARGE MACHINING OF AL-FE-SI ALLOY COMPOSITES USING TAGUCHI TECHNIQUE AND REGRESSION ANALYSIS.

Authors :
SENTHAMARAI, K.
SELVAKUMAR, S.
KANNAN, SATHISH
ALAGARSAMY, S. V.
Source :
Surface Review & Letters. Mar2024, Vol. 31 Issue 3, p1-11. 11p.
Publication Year :
2024

Abstract

Wire cut electric discharge machining (WCEDM) is a flexible and more essential for the precise machining of hard materials like composites and super alloys. In order to improve the surface texture as the main focus of the WCEDM process, the expansion of the fundamental procedural perceptive is very important. This paper mainly focuses on the prediction of surface quality of Al-Fe-Si alloy (AA8011) matrix composites during the WCEDM process. For the fabrication of composites, the varying proportions (0, 5, 10 and 15 wt.%) of ZrO2 ceramic particle were incorporated with AA8011 matrix alloy by using stir casting method. In the machining studies, to investigate the effects of reinforcement (wt. %) and the WCEDM process parameters, namely pulse current (amps), pulse-on time (μ s) and pulse-off time (μ s) on machining performance like surface roughness (SR) of the proposed composites. Based on the selection of parameters and their levels, an L16 (44) orthogonal array was most suitable for conducting the WCEDM experiments. A Taguchi technique was employed in this study to determine the optimal conditions of machining parameters through the signal-to-noise (S/N) ratio analysis. The result shows that the minimum SR is achieved at 5 wt.% of reinforcement, 6 amps of pulse current, 110 μ s of pulse-on time and 50 μ s of pulse-off time, respectively. Analysis of variance (ANOVA) results revealed that the reinforcement wt.% has the primary significant factor on SR, trailed by pulse-on time and pulse current, respectively. Furthermore, the regression equation was also developed to predict the SR and that values well agree with the experimental SR. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0218625X
Volume :
31
Issue :
3
Database :
Academic Search Index
Journal :
Surface Review & Letters
Publication Type :
Academic Journal
Accession number :
175994512
Full Text :
https://doi.org/10.1142/S0218625X24500197