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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Kumar, Rakesh
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (22/22 displayed)
- 2024Modelling the mechanical properties of concrete produced with polycarbonate waste ash by machine learningcitations
- 2024Modulation of the optical and transport properties of epitaxial SrNbO3 thin films by defect engineering
- 2024Nonlinear finite element and machine learning modeling of tubed reinforced concrete columns under eccentric axial compression loadingcitations
- 2023Establishment of magneto-dielectric effect and magneto-resistance in composite of PLT and Ba-based <i>U</i>-type hexaferritecitations
- 2023Nonlinear finite element and analytical modelling of reinforced concrete filled steel tube columns under axial compression loadingcitations
- 2022Coupled diffusion-mechanics framework for simulating hydrogen assisted deformation and failure behavior of metalscitations
- 2022Effect of reinforcement and sintering on dry sliding wear and hardness of titanium – (AlSi)0.5CoFeNi based compositecitations
- 2022Influence of laser texturing pre-treatment on HVOF-sprayed WC-10Co-4Cr+GNP coatings on AISI 304citations
- 2021Gaussian Distribution-Based Machine Learning Scheme for Anomaly Detection in Healthcare Sensor Cloudcitations
- 2020Tight Oil from Shale Rock in UAE: A Success Story of Unconventional Fracturingcitations
- 2019Some Preliminary Experimental Investigations on Inconel-718 Alloy with Rotary Tool-Electrode Assisted EDMcitations
- 2019Analysis of Dimensional Accuracy (Over Cut) and Surface Quality (Roughness) in Electrical Discharge Machining of Inconel-718 Alloycitations
- 2019Fabrication of an amyloid fibril-palladium nanocomposite: a sustainable catalyst for C–H activation and the electrooxidation of ethanolcitations
- 2013Dielectric, mechanical, and thermal properties of bamboo–polylactic acid bionanocompositescitations
- 2013Hallmarks of mechanochemistry: from nanoparticles to technologycitations
- 2010Bamboo fiber reinforced thermosetting resin composites: Effect of graft copolymerization of fiber with methacrylamidecitations
- 2010Influence of chemical treatments on the mechanical and water absorption properties of bamboo fiber compositescitations
- 2009Studies on water absorption of bamboo‐epoxy composites: Effect of silane treatment of mercerized bamboocitations
- 2009The Studies on Performance of Epoxy and Polyester-based Composites Reinforced with Bamboo and Glass Fiberscitations
- 2009Effect of Silanes on Mechanical Properties of Bamboo Fiber-epoxy Compositescitations
- 2009Graphene made easy: High quality, large-area samples
- 2008Enhanced Mechanical Strength of BFRP Composite Using Modified Bambooscitations
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article
Some Preliminary Experimental Investigations on Inconel-718 Alloy with Rotary Tool-Electrode Assisted EDM
Abstract
<jats:p>In this paper, some preliminary experimental investigations have been reported for analysing the machining performance characteristics viz. Material Removal Rate (MRR) & Tool Wear Rate (TWR). Electrical Discharge Machining (EDM) of Inconel-718 alloy via helical threaded cryogenically treated rotary copper tool electrode is conducted. Impact of machining factors viz. peak current (I<jats:sub>p</jats:sub>), pulse-on time (T<jats:sub>on</jats:sub>), tool rotation (N<jats:sub>t</jats:sub>) & hole depth (h) were investigated using Taguchi’s L<jats:sub>9</jats:sub> (3<jats:sup>4</jats:sup>) Orthogonal Array (OA). Optimum arrangements of factors for greatest MRR & least TWR were found in current study. Results predicts that I<jats:sub>p</jats:sub> & N<jats:sub>t</jats:sub> are two most affecting machining factors that affects MRR. Whereas I<jats:sub>p</jats:sub> & T<jats:sub>on </jats:sub>are two most affecting machining factors that affects TWR.</jats:p>