Optimization Approach of Turning Process of Multiwalled Carbon Nanotubes-Aluminium Oxide/Epoxy Hybrid Nanocomposites

The high quality of the machined parts in a short time is a research challenge for enhancing these parts’ operating performance. Optimizing the machining operations and adequately selecting the cutting parameters can solve this challenge. Thus, this work proposes an optimization approach of the machining process parameters of epoxy hybrid nanocomposites reinforced by multiwall carbon nanotubes (MWCNTs) and aluminum oxide (Al₂O₃). Cutting speed (V), feed rate (F), insert nose radius, and depth of cut (D) were the machining parameters. The roundness error and surface roughness (Ra) were selected as process response control parameters. The optimization techniques such as response surface method (RSM) and grey relation analysis (GRA) with the variance of analysis (ANOVA) were involved. Forty experimental runs were performed. The RSM optimization and ANOVA results showed that the insert nose radius and F are the most significant factors that affect the Ra. Besides, the F is the most significant factor that affects the roundness error. V = 1000 mm/min, F = 0.08 mm/rev, insert nose radius of T1 = 0.8 mm, and D = 1 mm are the optimum values of the process parameters based on GRA for roundness errors and Ra.