Modeling and Experimental Investigation of Abrasive Jet Machining of Glass | ||||
Port-Said Engineering Research Journal | ||||
Article 13, Volume 20, Issue 1, March 2016, Page 127-137 PDF (1.07 MB) | ||||
Document Type: Original Article | ||||
DOI: 10.21608/pserj.2016.33656 | ||||
View on SCiNiTO | ||||
Authors | ||||
El Shimaa Abdelnasser 1; Ahmed Elkaseer2; Ahmed Nassef3 | ||||
1Demonstrator of Production Eng., Faculty of Eng., Port Said University | ||||
2Assistant Prof. of Production Eng., Faculty of Eng., Port Said University | ||||
3Professor, Department of Production Engineering and Mechanical Design, Faculty of Engineering, Port Said University, Port Said, Egypt | ||||
Abstract | ||||
This paper presents a modeling approach implemented to consider the effects of the process parameters of Abrasive Jet Machining (AJM), namely applied pressure (Pr), standoff distance (SoD), nozzle diameter (dn) and particle grain size (dg) on machining performance. In particular, a previously reported model of the AJM was adapted to improve its capability to predict material removal rate (MRR) more accurately. In order to validate the developed model experimentally and at the same time to examine the influence of the machining conditions on the MRR, a series of drilling tests have been carried out on glass workpieces using sand as an abrasive powder. After each cutting trial, the MRR was quantified which enabled characterizing the influence of the applied process parameters on the machining performance in terms of resultant MRR. In addition, the experimental results were compared with those obtained by the proposed model, where a relatively acceptable agreement between both results was achieved with an average error of 39%. Also, the experimental results have revealed that MRR is highly dependent on the kinetic energy of the abrasive particles and the applied pressure was found to be the most significant parameter that dominated the material removal rate | ||||
Keywords | ||||
AJM; MRR; process conditions; modeling; experimental validation | ||||
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