Modelling and Optimization of the Cutting Forces During Ti6al4v Milling Process Using the Response Surface Methodology and Dynamometer

Abstract

The measurement of cutting forces using highly sensitive piezoelectric force sensors is significant in the optimization of the machining process. In this study, the modelling and optimization of the cutting forces during the milling process of Ti6Al4V was carried out using the Response Surface Methodology (RSM) and the dynamometer. The ranges of the process parameters are: cutting speed (250-280 mm/min), feed per tooth (0.06-0.24 mm) and axial depth of cut (0.30-3.0 mm) are varied over four levels while cutting force serves as the response of the designed experiment. The physical experiments were carried out using a DMU80monoBLOCK Deckel Maho 5-axis CNC milling. Three sets of 2-flute, 10 mm corner radius mills was used for the machining operation. A solid rectangular work piece of Ti6Al4V was screwed to the stationary dynamometer (KISTLER 9257A 8-Channel Summation of Type 5001A Multichannel Amplifier) mounted directly to the machine table. Milling operations were performed using different cutting parameters of cutting speed, feed per tooth and depth of cut and data were collected through Data Acquisition (DAQ) connected to the computer. The numerical experiment produced a mathematical model for predicting the values of the cutting forces as a function of the independent process parameters while the physical experiment revealed that the piezoelectric sensor is highly sensitive to variations in the values of the cutting force.

Review of life cycle models for enhancing machine tools sustainability: lessons, trends and future directions

“…The limitation being that the cooling action of the compressed air is usually less efficient under high speed cutting operation as well as cutting operation involving materials with high heat retention capacity such as titanium due to its low thermal conductivity ( Zhao et al., 2007 ; Daniyan et al., 2019d ). Furthermore, the use of nano-fluids been widely reported in reducing the cutting temperature, heat and friction.…”

Process Design, Development and Mechanical Analysis of Cu-Zn Alloy Produced by Sand Casting Process

“…The RSM and CCD has the capability to identify the feasible combinations of process parameters and manufacturing conditions as well as their cross effects on the response of the designed experiment. In addition, the RSM can suitably study the interactive effects of the process parameters or conditions (independent variables) on the experimental response (dependent variables) [32][33][34]. For the purpose of this study, the annealing temperature and the percent content of the zinc were the two factors considered as the independent variables A and B respectively while the hardness and the tensile strength of the brass stand as the response (output) of the designed experiment.…”

DEVELOPMENT OF NUMERICAL MODELS FOR THE PREDICTION OF TEMPERATURE AND SURFACE ROUGHNESS DURING THE MACHINING OPERATION OF TITANIUM ALLOY (Ti6Al14V)

“…Several methods, such as the analytical and numerical methods icluding the Taguchi, Response Surface Methodology, Artificial Neural Network (ANN) etc. have been proposed for the prediction of the temperature and other process parameters during the cutting operations [17][18][19][20][21]. This is because aforementioned approaches have proven to be suitable for the modelling and prediction of important process parameters and also capable of reducing the numbers of expensive physical experimentation runs.…”