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Influence of grinding parameters on surface roughness and temperature under carbon nanotube assisted MQL

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TLDR
In this paper , the effects of hard grinding with key focus on temperature, surface roughness and chips morphology under the application of CNT-mixed MQL and compressed air were studied.
Abstract
ABSTRACT Conventional flood cooling system has some environmental and economic issues. Minimum quantity lubrication (MQL) has been established as a better strategy to control the machining temperature than conventional flood cooling system. Integrated use of carbon nanotube (CNT) with MQL has been drawing attention in recent times. The purpose was to study the effects of hard grinding with key focus on temperature, surface roughness and chips morphology under the application of CNT-mixed MQL and compressed air. The hardness of work material (AISI 1060 steel) was varied at three values (40, 45 and 50 HRC) with the variation of fluid flow rates and infeed rates to observe the machining behaviour. Experimental plan was established using full factorial design of experiment while mathematical models and optimisation were constructed following response surface methodology (RSM). Optimum output responses were flow rate 75 ml/h, infeed (depth of cut) 10 µm and hardness of material is from 40 to 45 HRC. Fluid flow rate of 75 ml/h resulted in best surface finish while work material of 40 HRC hardness generated lowest temperature while machining. A lower hardness values and a moderate flow rate produced favourable machining outcomes, i.e. lower temperature and improved surface finish.

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References
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A review on applications and challenges of nanofluids

TL;DR: It has been found nan ofluids have a much higher and strongly temperature-dependent thermal conductivity at very low particle concentrations than conventional fluids, which can be considered as one of the key parameters for enhanced performances for many of the applications of nanofluids.
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The Relationship Between Variable Selection and Data Agumentation and a Method for Prediction

TL;DR: It is shown that data augmentation provides a rather general formulation for the study of biased prediction techniques using multiple linear regression and a way to obtain predictors given a credible criterion of good prediction is proposed.
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Effect of minimum quantity lubrication (MQL) on tool wear and surface roughness in turning AISI-4340 steel

TL;DR: In this article, the role of minimum quantity lubrication (MQL) on tool wear and surface roughness in turning AISI-4340 steel at industrial speed-feed combination by uncoated carbide insert was investigated.
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Effects of minimum quantity lubrication on turning AISI 9310 alloy steel using vegetable oil­based cutting fluid

TL;DR: In this article, minimum quantity lubrication (MQL) was provided with a spray of air and vegetable oil to reduce the cutting zone temperature enabling favorable chip formation and chip-tool interaction.
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Experimental Evaluation of the Lubrication Performance of MoS2/CNT Nanofluid for Minimal Quantity Lubrication in Ni-based Alloy Grinding

TL;DR: In this article, a hybrid nanofluid consisting of MoS2 nanoparticles with good lubrication effect and CNTs with high heat conductivity coefficient is investigated for Ni-based alloy grinding.