A Study on Deviations of the Jet with Traverse Speeds on Different Materials in Pocket Milling Using Abrasive Water Jet Machining Process

2013 ◽  
Vol 372 ◽  
pp. 402-405 ◽  
Author(s):  
T.V.K. Gupta ◽  
J. Ramkumar ◽  
Puneet Tandon ◽  
N.S. Vyas

The current trend in abrasive water jet machining process is getting focused on milling applications using this technique. Abrasive water jet machining (AWJM) process is a well defined process for cutting or part separation. The present paper reports on the geometry obtained in controlled depth milling process of different materials. The dimensions considered in this paper are the pocket depth and the change in the kerf profile. Experimental observations are made relating the kerf profile with traverse speed and the mechanical properties of the work piece material. Tool paths for obtaining the pocket of size 9 mm x 20 mm are generated in raster mode and machined using AWJM on materials of varying hardness and at different traverse speeds. It is observed that there is a significant change in the geometry of the kerf profile and also the depth of the pocket with speed in conjuction with the material hardness.

2021 ◽  
Author(s):  
Sabarinathan Palaniyappan ◽  
Annamalai Veiravan ◽  
Rajkumar Kaliyamoorthy ◽  
Vishal Kumar

Abstract Increasing demand and resource overuse has prompted the exploration of spent secondary materials as a primary raw material for a variety of applications, leading to a more sustainable environment. Spent electric grid ceramic insulator, one of the waste materials of ceramic industry has a good hardness and strength. It can be reused as value added material in Abrasive Water Jet Machining (AWJM) industry. This present work deals with conversion of electric insulator rejects (EIR) into a cost-effective replacement material for abrasive water jet machining process. Mechanical crushing method is opted to generate the abrasive grit for the machining process. Grit generation pattern and the friability of the electric insulator rejects were determined experimentally. The results indicate that the friability of the processed electric insulator rejects is comparable with the commercially available garnet abrasive. Geometric parameters such as sphericity, elongation ratio, and shape factor for the processed electric insulator rejects were studied using scanning electron microscopy. The machining performance indicators for standard aluminium material such as volume of material removal, kerf angle, surface roughness and cutting width were measured for electric insulator rejects and compared with existing garnet abrasive grain. The experimental results of newly generated electric insulator reject abrasive were matched with performance indicators of the garnet abrasive. The observed deviation was lower proving that it can be used as alternative abrasive in the abrasive jet machining process. Cost analysis and recycling ability predict the economical usability of the newly generated abrasives.


Author(s):  
KSK Sasikumar ◽  
KP Arulshri ◽  
K Ponappa ◽  
M Uthayakumar

Metal matrix composites are difficult to machine in traditional machining methods. Abrasive water jet machining is a state-of-the art technology which enables machining of practically all engineering materials. This article deals with the investigation on optimization of process parameters of abrasive water jet machining of hybrid aluminium 7075 metal matrix composites with 5%, 10% and 15% of TiC and B4C (equal amount of each) reinforcement. The kerf characteristics such as kerf top width, kerf angle and surface roughness were studied against the abrasive water jet machining process parameters, namely, water jet pressure, jet traverse speed and standoff distance. Contribution of these parameters on responses was determined by analysis of variance. Regression models were obtained for kerf characteristics. Contribution of traverse speed was found to be more than other parameters in affecting top kerf width. Water jet pressure influenced more in affecting kerf angle and surface finish. The microstructures of machined surfaces were also analysed by scanning electron microscopy. The scanning electron microscopy investigations exposed the plastic deformation cutting of hybrid 7075 aluminium metal matrix composite. X-ray diffraction analysis results proved the non-entrapment of abrasive particle on the machined surface.


Materials ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 7768
Author(s):  
Adam Štefek ◽  
Martin Tyč

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.


Author(s):  
ABHIMANYU K. CHANDGUDE ◽  
SHIVPRAKASH B. BARVE

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.


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