A mathematical modelling of Abrasive Waterjet Machining on Ti-6Al-4V using Artificial Neural Network

Abstract Ti-6Al-4V is classified among the most commonly used Ti-alloys and is extensively used in aerospace and medical industries where low-density, high strength and outstanding corrosion resistance are required. This material cannot be processed by conventional machining methods because of its high strength. Abrasive Waterjet Machining, abbreviated as AWJM, is an unconventional machining process suitable for machining Ti-6Al-4V as it generates less heat affected zone. The quality of AWJM is governed by process parameters, the selection of these parameters is critical in this technology to achieve the desirable output measures. This paper provides an experimental investigation for the performance analysis of process parameters on machining Ti-6Al-4V using abrasive waterjet technology. In order to select appropriate parameters, a mathematical equations were developed using Regression Investigation Method (RIM) Artificial Neural Network (ANN) procedures. Based on the input and output data collected from the experiments, modelling is done and tested for the different set of data to ensure the accuracy. These mathematical models can be used to identify the static and dynamic behavior of the process. These models will further help in simulating the process, expanding the design facilities and studying the physical and chemical variation in the process. Models provide understanding the operations, control methods and the possible optimization. The developed models also help in documenting the performance of the existing system.