Multi-Response Optimization of the Tribological Behaviour of PTFE-Based Composites via Taguchi Grey Relational Analysis

Abstract

Polymer-based composites find applications in several areas because of their exceptional properties. This article deals with Taguchi grey relational optimization method of abrasive parameters (load (L), grit size (G) and sliding distance (D)) and their influence on abrasive performance of reinforced polytetrafluoroethylene (PTFE) composites. A Taguchi L9 orthogonal array was designed, and nine experimental tests were conducted based on the Taguchi designed experiments. A pin-on-disc tribology machine was used for the experiments. The coefficient of friction (µ) and abrasive specific wear rate (Aw) were recorded for each experiment. An analysis of variance (ANOVA) was performed to establish the significance and percentage contribution of each parameter affecting the abrasive wear performance. Results from the Taguchi-grey-relational method showed that the optimal combination of parameters was achieved at load of 10 N, grit size of 1000 mesh, and sliding distance of 350 m (coded as L3G1D3). ANOVA findings revealed that a grit size with 67.69 % as the most influential on the abrasive performance of polymer-based composites. Validation tests performed using the optimal combination parameter showed an enhancement of 55.22 % in grey relational grade.