2019
DOI: 10.31614/cmes.2019.04924
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Finite Element Modeling in Drilling of Nimonic C-263 Alloy Using Deform-3D

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Cited by 7 publications
(5 citation statements)
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“…According to Arrazola et al [12], the 3D-FEM enabled by high-end computing systems provide better visualization and understanding of the cutting operations. Drilling is the one cutting process that has been widely studied with the use of 3D-FEM [13][14][15][16][17][18]. Due to the nature of the drilling process and the complexity of the tools involved, threedimensional simulations proved to be valuable assets when studying the phenomena that occur during drilling.…”
Section: Introductionmentioning
confidence: 99%
“…According to Arrazola et al [12], the 3D-FEM enabled by high-end computing systems provide better visualization and understanding of the cutting operations. Drilling is the one cutting process that has been widely studied with the use of 3D-FEM [13][14][15][16][17][18]. Due to the nature of the drilling process and the complexity of the tools involved, threedimensional simulations proved to be valuable assets when studying the phenomena that occur during drilling.…”
Section: Introductionmentioning
confidence: 99%
“…It was also reported that the temperature and the SR increased with a lower coolant pressure and nanoparticle concentration [87]. Nagaraj et al [88] developed a FEMbased simulation model to predict the force and temperature generated during the drilling of Nimonic C263 using a coated carbide drill bit. The study concluded that the temperature distribution at the cutting-edge increases with an increase in point angle and spindle speed.…”
Section: Drillingmentioning
confidence: 99%
“…The prediction of the machining attributes in advance would reduce the machining cost resulting from unidentified level of machining parameters; hence a suitable predictive model is required to predict the machining attributes [1]. Since the precision of the simulated outcome is entirely dependent on the process variables, it is important to understand the effects of different levels of process variables employing appropriate statistical models on turning any materials [2].…”
Section: Introductionmentioning
confidence: 99%