Machinability study of Aluminium 6082 reinforced with boron carbide and titanium by stir casting method using Abrasive water jet machining process

Aluminium Metal Matrix Composite (AMMC) has broad uses in the medical, aerospace, and automobile industries, which have long sought lightweight materials with superior designs and improved properties to improve performance. This analysis has aimed to prepare an AMMC to investigate its machining and mechanical properties. The AMMC is produced using a stir casting process by reinforcing boron carbide and titanium with aluminium 6082. The material's mechanical properties are studied by using wear test, hardness test, and corrosion test. The wear rate increases when the load increases by varying the load and time with speed as a constant. It is found that the hardness of a material is increased due to titanium and boron carbide as the reinforcement particle in the fabricated AMMC. Using the pitting corrosion technique, the corrosion occurs on the AMMC under the estimated time at room temperature. In order to illustrate the machining characteristics of the aluminium metal matrix composite, an abrasive water jet machining process has been used. The experiments use L9 orthogonal Array using Taguchi's method and ANOVA analysis. The input parameters considered are Traverse rate, Stand-off distance, and Nozzle diameter. To find the optimum value of circularity, cylindricity, and surface roughness by varied input parameters. The respective graphs are also plotted. Scanning electron microscopic analysis was performed on the wear-tested specimen and machining surface of the material to determine the distribution of reinforced material and investigate the material's fracture mechanism. It is found that wear tracks, voids, delamination, micro pits, embedded garnet abrasive particles are located on the machined surface of the AMMC.

MODELING AND MULTI-RESPONSE OPTIMIZATION OF ABRASIVE WATER JET MACHINING USING ANN COUPLED WITH NSGA-II

This paper aims to develop a predictive model and optimize the performance of the abrasive water jet machining (AWJM) during machining of carbon fiber-reinforced plastic (CFRP) epoxy laminates composite through a unique approach of artificial neural network (ANN) linked with the nondominated sorting genetic algorithm-II (NSGA-II). Initially, 80 AWJM experimental runs were carried out to generate the data set to train and test the ANN model. During the experimentation, the stand-off distance (SOD), water pressure, traverse speed and abrasive mass flow rate (AMFR) were selected as input AWJM variables and the average surface roughness and kerf width were considered as response variables. The established ANN model predicted the response variable with mean square error of 0.0027. Finally, the ANN coupled NSGA-II algorithm was applied to determine the optimum AWJM input parameters combinations based on multiple objectives.

Impact of Preparation of Titanium Alloys on Their Abrasive Water Jet Machining

Several titanium alloys, i.e., grade 2 Ti, Ti6Al4V and NiTi alloy, prepared by selected deformation procedures were subjected to abrasive water jet (AWJ) cutting and subsequently analysed. The study describes samples’ preparations and respective material structures. The impact of deformation processing of the selected alloys on the declination angle during cutting, and the results of measurements of surface wall quality performed for the selected samples at the Department of Physics of Faculty of Electrical Engineering and Computer Science at VŠB–Technical University of Ostrava, are presented and discussed, as are also the influences of structural features of the processed titanium alloys on surface qualities of the investigated samples. The results showed that the highest resistance to AWJ machining exhibited the Ti6Al4V alloy prepared by forward extrusion. Its declination angle (recalculated to the thickness 10 mm to compare all the studied samples) was 12.33° at the traverse speed of 100 mm/min, pumping pressure of 380 MPa, and abrasive mass flow rate of 250 g/min.

3D EVALUATION OF THE TOPOGRAPHY OF THE SURFACE BY ABRASIVE WATER JET MACHINING TECHNOLOGY

The article deals with contact and non-contact evaluation of surface roughness created by water jet cutting technology (AWJ). Non-contact surface measurement was performed using an LPM laser profilometer. The values measured by the laser profilometry method were compared with the values measured by the contact method, the Mitutoyo SJ 400 roughness meter. Six samples were produced. Three in stainless steel and three in structural steel. In order to achieve a different surface topography, different feed rates of the cutting head were used on the samples, which was reflected in the quality of the resulting surface. The evaluated parameters were the average arithmetic deviation of the assessed profile and the largest height of the profile inequality.