Optimization of drilling parameters using GRA for polyamide 6 nanocomposites

ABSTRACT

For drilling polyamide 6 (PA6) hybrid nano composites reinforced with copper nanoparticles and multi-walled carbon nano tubes (MWCNT), this work optimizes the process variables including reinforcing percentage, drill bit diameter, feed rate, and spindle speed. In this work, the Taguchi method was used to construct the experiments. L9 orthogonal arrays were used in the trials. Torque, surface roughness, and thrust force were the three different responses on which the influence of different process factors and their combinations were examined. The ideal values of the process factors have been found by employing the grey relational code produced by the grey relational analysis. The crucial process factors were identified using analysis of variance (ANOVA). To verify the test results, a confirmation test was carried out. The surface of the drilled holes was examined with a scanning electron microscope. The optimal drilling process parameters for PA 6 nanocomposites were 0.6 weight %, 500 rpm, 90 mm/min, and 6 mm in drill diameter. The weight percentage of the nano Cu particles (60.618%) clearly has a greater impact on drilling of Polyamide 6 hybrid nanocomposites reinforced with Cu nanoparticles and MWCNT than did the drill diameter (26.699%), speed (7.407%), and feed rate (5.271%). Verification of testing results at the best standard shows that the thrust force is reduced from 288.8 N to 281.4 N, the torque is decreased from 27.01 Nm to 24.52 Nm, and the surface polish is improved from 1.414 to 1.23 μm.

Keywords
Polyamide 6 (PA6); Multi Walled Carbon Nanotubes; Copper nano particles; Taguchi; Grey Relational Analysis