Modelling and Analysis of Wear Prediction in Machining of Nano Based GFRP Composites Using RSM

Autor: Godwin Jose, S. Alexraj, A. Saravanapandi Solairajan, P. Vijaya Rajan
Rok vydání: 2015
Předmět:
Zdroj: International Journal of Engineering Research in Africa. 20:3-11
ISSN: 1663-4144
DOI: 10.4028/www.scientific.net/jera.20.3
Popis: Glass fiber reinforced composite material was fabricated using E-glass fiber with unsaturated polyester resin. In Glass Fiber Reinforced Plastic (GFRP) composites, the matrix of polymer is reinforced with glass fibers. The surface quality and dimensional precision significantly affect the parts during their suitable life, particularly in cases where the components come in contact with other elements or materials. In the current study, GFRP is machined with two cases i.e. with and without Nano combinations in lathe. These machining studies were carried out on lathe using three different cutting tools: namely Carbide (K-20), Cubic Boron Nitrate (CBN) and Polycrystalline Diamond (PCD). The cutting parameters considered were cutting speed, feed, and depth of cut. Surface Finish is the most important parameter measured by main spindle and compares the value with another. A second order mathematical model in terms of cutting parameters was developed using RSM. The results specify the developed model is suitable for prediction of surface roughness in machining of GFRP composites.
Databáze: OpenAIRE