الفهرس 
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Abstract
The high quality of the machined components is a research challenge to
improve the operational efficiency of such components. This problem can be
overcome by optimizing machining operations and choosing the cutting parameters correctly. Therefore, this work proposes an optimization approach to the process, cutting parameters of epoxy hybrid nanocomposites strengthened by multi-walled
carbon nanotubes (MWCNTs) and aluminum oxide (AL2O3) with 1% by volume of
each by mechanical stirring technique. The selected machining parameters were feed rate (F), insert nose radius, rotational speed (n), and cut depth (a). Metal removal rate (MRR), roundness error and surface roughness (Ra) were selected as parameters
for the process response control. Optimization techniques involved were the response surface method (RSM) and analysis of Variance (ANOVA) coupled with grey relation analysis (GRA). The results of RSM optimization and ANOVA showed that the most important factors influencing Ra were the insert nose radius and feed rate, and for roundness were the feed rate then the rotational speed and for metal
removal rate were feed rate, depth of cut and rotational speed. Based on grey relation analysis (GRA), the insert type t1 (nose radius of 0.8 mm), the rotational speed of
2000 rpm, the feed rate of 0.08 mm/rev, and depth of cut 1 mm were the optimal turning process parameters for machining this material. In addition, the feed rate and the depth of cut are the significant parameters. from the error analysis results, the
accuracy of error analysis for the minimum roundness error with both inserts was 80.565, for minimum Ra was 90.03% and for grey relation analysis was 83.55%. KEYWORDS: Metal Removal Rate, Surface Roughness, Response Surface Method (RSM), Turning, Hybrid Nanocomposite.