Taguchi optimization of process parameters used for improving tribological behaviour of graphene nanoparticle dispersed nanolubricant

Autor: K Veera Raghavulu, N Govindha Rasu
Rok vydání: 2022
Předmět:
Zdroj: Engineering Research Express. 4:015024
ISSN: 2631-8695
DOI: 10.1088/2631-8695/ac54ec
Popis: Graphene nanoparticle has gained much attention in recent years as a potential additive to base oil, used for lubrication. In this scenario, the current study is aimed at analyzing the influence of process parameters such as concentration of graphene nanoparticles in Polyolester (POE) oil, sliding velocity and applied load upon the tribological behavior of POE oils with graphene nanoparticle-based additive. A robust Taguchi method was applied to optimize the selected process parameters and identify the best combination of the chosen factors. XRD and SEM analyses were conducted to characterize the graphene nanoparticles. Taguchi method was applied and pin-on-disc type test was conducted to assess the friction and wear properties. Analysis of variance (ANOVA) was conducted to analyze the significance of control factors considered (R2 = 98%). The average coefficient of friction value was found to be around 0.051, whereas average S/N ratio value was calculated as 26.15. The current study found the optimum control factors to be 0.05% graphene nanoparticles, with 50 N applied load at a sliding velocity of 3.6 m s−1.
Databáze: OpenAIRE