Experimental Analysis and ANN Modelling of HAZ in Laser Cutting of Glass Fibre Reinforced Plastic Composites. (2016)

• Record Type: Journal Article
• Authors: Patel, Pathik; Sheth, Saurin; Patel, Tejas
• Is Part Of: Procedia technology. Volume 23(2016)
• Page Start: 406
• Page End: 413
• Publication Date: 2016
• Subjects: Composite Materials -- Laser Cutting -- HAZ -- Artificial Neural Network -- Regression; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.03.044
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: Composite materials increasingly being used in aeronautics, aerospace, automotive and marine industries due to their high strength to weight ratio. Machining of composite material is difficult by conventional machining methods but laser cutting can offers an alternative machining method in which quality cut can be obtain by controlling different process parameters. The aim of the present research is to investigate the effect of laser cutting parameters viz. Laser Power, Cutting Speed and Gas Pressure on the response parameter HAZ. Optimization of the process parameters, their levels and combinations are decided on the basis of Taguchi L27 Orthogonal array and subsequently predictive models have been developed using Second Order Regression and Artificial Neural Network (ANN) modelling techniques. Analysis of Variance (ANOVA) is then carried out to find the relative influence of process parameters on HAZ. After comparing the simulated data with experimental data, the ANN model shows better agreement for predicting HAZ with more than 97% of accuracy for the given range of input parameters.