Multiresponse optimization of fabrication variables of α-MnO₂-epoxy nanocomposite through simulation-based Taguchi-grey relational analysis

A simulation-based Taguchi-grey relational analysis was applied in this research to explore the influence of fabrication variables on multiple responses: mass density, microhardness, and specific wear rate of the α-MnO₂-epoxy nanocomposite. The tests were conducted with five controlled processing variables: stirring time, presonication time, tip-sonication time, pulse-on time, and curing temperature. The responses were verified using a simulation technique. Confirmatory testing was performed to ensure the accuracy of the test results. X-ray diffraction, scanning electron microscopy, and energy-dispersive X-ray techniques indicated the formation of α-MnO₂. The main effect plots indicated that the experiment was conducted with the stirring time of 30 min, presonication time of 420 min, tip-sonication time of 60 min, pulse-on time of 20 s, and curing temperature of 60 °C, which was the optimal setting for the variables affecting the responses. Results showed that the tip-sonication time, which accounted for 91.91 % of the signal-to-noise ratio of grey relational grade, correlated better with responses. The experimental mass density, microhardness, and specific wear rate of the nanocomposites under optimal manufacturing conditions were 1.2447 g/cm³, 22.32 kgf/mm², and 34.29×10⁻⁵ mm³/Nm, respectively. The relative increase in grey grade over the initial optimal setting was 9.39 %. The simulated models facilitated the evaluation of experimental response data. As a result, the simulation-based methodology related to the Taguchi-grey procedure improved the performance features of the nanocomposite.