PREDICTION OF FORCES AND DAMAGE IN MACHINING OF COMPOSITES USING ARTIFICIAL INTELLIGENCE

Abstract

GFRP is an immensely versatile material, which is lightweight and has inherent strength to provide a weather resistance finish, with a variety of surface texture and an unlimited colour range available. Therefore it is used in immense number of applications such as storage tanks, buildings, piping etc. These applications require drilling of GFRP laminates in order to prepare various types of assemblies and hence quality drilling is of paramount concern in this material. The present research endeavour is to design and develop an artificial intelligent tool to predict the drilling induced damage during machining (drilling) of fibre reinforced plastics (FRP) laminates. Generally, the user faces the dilemma about how to set the input parameters in order to ensure a smooth and good quality drilling. The graphical user interface (GUI) developed in this dissertation work serves as the artificial intelligent tool which return the values of delamination factor, thrust force and torque for given set of inputs. Thus, the user can check that for a particular value of input such as drill geometry, cutting speed, drill diameter and feed rate, what would be the damage caused to the drill hole. Moreover, the GUI integrates adaptive systems into it, ensuring that with time as more and more number of experimental data is collected for training of tool, the more it will become accurate and close to practical results. The user interface developed can also be used to compare the amount of drilling damage at two different set of drilling input parameters and thus the input parameters which will lead to minimization of damage and process optimization can be found out.