4.5 Article

Selection of optimal processing condition during WEDM of compocasted AA6061/cenosphere AMCs based on grey-based hybrid approach

期刊

MATERIALS AND MANUFACTURING PROCESSES
卷 33, 期 14, 页码 1549-1558

出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/10426914.2018.1453154

关键词

ANOVA; desirability; GRSM; microstructure; WEDM

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Investigation on the machining of Aluminium Matrix Composites (AMCs) through non-conventional approach are the current attention over the conventional machining approach of those may produces additional complexity in industrial manufacturing. The current research focused on investigating the machinability characteristics of the newly prepared compocasted AA6061/cenosphere AMCs implementing a non-traditional material removal process via spark erosion called Electro Discharge Machining (Wire-EDM). The performance measure of the system for the different combinations of independent process variables were considered as cutting rate (CR), Kerf Width (KW) and Surface Roughness (SR). Experimental design were carried out based on Response Surface Methodology (RSM) employed face centered Central Composite Design (CCD) required for the analysis. A hybrid approach comprises of grey relation theory in conjunction with RSM Grey-Response Surface Methodology (GRSM) were executed for the prediction of optimal settings of machining condition which yield the optimum performance characteristics of the system. The model fit summary revealing an adequate fitness of the developed model to the actual system, as the R-square value was found to be 0.9607, close to unity and a larger (< 4.0) adequate precision value of 20.87. Noticeable improvement were attained on cutting speed (3.234%), kerf width (2.7415%) and surface roughness (7.053%) implementing the optimal setting of machining parameters based on the proposed hybrid GRSM approach. Generous improvement was also noticed on the 3D optical Wire Electro Discharge (WED) machined surface texture demonstrating the quality of surface roughness and texture using hybrid GRSM predicted processing conditions.

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