Multiresponse Optimization of Wear Parameters of Steel-Embedded Glass-Epoxy Hybrid Composites Using Taguchi-Grey Method Optimization

Abstract

Abstract In this work, Taguchi-grey relational analysis (GRA) has been used to optimize the process parameters during the tribological performance of steel-embedded glass-epoxy hybrid composites. The specific wear rate (SWR) and the average coefficient of friction (CoF) were investigated. The tribological test was planned by using Taguchi L27 orthogonal array. The tests were carried using different factors like steel volume % (0–10 %), applied load (80–100 N), and sliding distance (1,000–2,000 m) for a constant time (20 min). The optimal process parameters were obtained with Taguchi-GRA, and the influencing factor was determined with the help of analysis of variance. The results show that the most influencing factor is steel volume %, followed by applied load and sliding distance. The dry sliding wear performance was optimized to achieving minimal SWR and average CoF. Steel volume 10 %, sliding distance 1,000 m, and applied load 80 N were observed as optimum parameters to achieving minimal SWR and average CoF. A confirmation test was carried out to verify the tests. The results show that the multiresponses such as SWR and average CoF were significantly enhanced through GRA. Finally, the worn surfaces of the hybrid composites were studied through scanning electron microscope (SEM). The SEM shows that the pits on the surface of the image were covered with voids and other defects. The SEM also shows that the specimen’s porosity decreases with the increasing fractional volume of steel in the composite.