Experimental investigation on material removal rate during abrasive water jet machining of GFRP composites

2020 ◽  
Vol 26 ◽  
pp. 1389-1392 ◽  
Author(s):  
Dharmagna R. Tripathi ◽  
Krupang H. Vachhani ◽  
Soni Kumari ◽  
Dinbandhu ◽  
Kumar Abhishek
2010 ◽  
Vol 135 ◽  
pp. 370-375 ◽  
Author(s):  
Jing Ming Fan ◽  
Chang Ming Fan ◽  
Jun Wang

Micro abrasive water jet (MAWJ) machining is a new promising micro machining technology for brittle material. The rate of material removal is one of the most important parameter for abrasive processes. Predictive mathematical model for the material removal rate is presented for micro channel machining by micro abrasive water jet (MAWJ). A dimensional analysis technique is used to formulate the model. The validity and predictive capability of the models are assessed and verified by an experimental investigation when machining glasses. It shows that the predictions of the models are in good agreement with the experimental data.


The main aim of this investigation is to study the abrasive water jet machining performance of the twill weaved carbon fibre reinforced epoxy composite. Abrasive water jet machining experiment was conducted as per L9 orthogonal array, by varying water pressure, transverse speed and SOD. The performance of the composite was analyzed by measuring the material removal rate and kerf. Using Taguchi analysis, the influences of input parameter over the output response was analyzed. It was found that the MRR is highly influenced by the transverse speed whereas kerf is highly influence by the SOD.


Author(s):  
Divyansh Patel ◽  
Puneet Tandon

This work presents a description of abrasive water-slurry jet machining (AWSJM) to improve machining capabilities of conventional abrasive water jet machine. The present work proposes a new approach of AWSJM by equipping the conventional abrasive water jet machine (AWJM) with a programmable servomotor controlled abrasive flow control valve and fabricating a setup for injecting polymer solution into the abrasive water jet nozzle, which improves the performance of abrasive jet. Three types of concentrations are prepared to perform the experiments at different values of pressure, abrasive flow rate and abrasive size. The present work identifies the optimal range of process parameters for AWSJM, with natural gelatin as binder, with the response parameters being material removal rate and kerf width. Gelatin produces a coherent, 4-phase beam which leads to efficient energy transfer, improved cutting efficiency, increased material removal rate, reduced kerf width, reduced diversification of jet and better control of abrasive flow rate. The investigation shows that materials removal rate (MRR) tends to increase for approximate 20% (by weight) concentration of polymer in AWSJM. If the polymer is mixed in lower quantities, the MRR is almost equal or less than the MRR for AWJM.


2018 ◽  
Vol 221 ◽  
pp. 01004
Author(s):  
Vishal S Sharma ◽  
Amit Kumar ◽  
Munish Kumar Gupta ◽  
Neeraj Bhanot

Recently, the trend of optimization algorithms for improvements of surface quality and productivity characteristics in abrasive water jet machining of titanium alloy (Ti-6Al-4V alloy) has become increasingly more widespread in various industrial sectors i.e., aircraft and automobile Industries. Here, the present research attempts to select the ideal or best AWJM process parameters by implementing the well known meta-heuristic algorithm i.e., Teacher learning based optimization method (TLBO). The AWJM experiments as per the Taguchi L9 orthogonal array were performed on Ti 6Al-4V titanium alloy by considering jet transverse speed, stand-off distance and abrasive flow as the input parameters. Then, the influence of process parameters on surface roughness and material removal rate has been performed by means plot and ANOVA analysis. After that, the results are optimized with the TLBO method. The overall results indicate that the TLBO method is an efficient method used to find the optimal results with very short interval of time i.e., within 3 sec.


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