Integrated Energy Use Optimisation and Cutting Parameter Prediction Model - Aiding Process Planning of Ti6Al4V Machining on the CNC Lathe

Abstract

This paper reports on the IEUOCPPTM (Integrated Energy Use Optimisation and Cutting Parameters Prediction Tool Model) designed to optimise the machining parameters planning process of titanium alloy machining on the CNC lathe. It aimed to create a novel systematic methodology for determination of optimised cutting parameters. MATLAB genetic algorithm and Visual Basic Application softwares were integrated to generate the IEUOCPPTM optimised machining process planning tool for titanium alloys. The empirical 18 full factorial experiment runs design was carried out using Minitab. Determination of appropriate cutting parameters is vital for conserving energy and achieving sustainability for the titanium alloy machining businesses confronted with immense pressure to produce cost-effectively in record delivery times. Machining is a fundamental, and electrical energy intensive, activity in the profiling process of cylindrical T-alloy, Ti6Al4V, components used in the aerospace, automotive and general metal working industries. Varied performance outcomes were achieved, on the machined components after predicting the input parameters using the tool as opposed to the good-guess approach currently being applied in industry. Validation experiments confirmed functionality of IEUOCPPTM in forecasting the cutting parameter settings required, to achieve desired responses during machining of Ti6Al4V within an average error range of 8%.