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Parametric and nonparametric description of the surface topography in the dry and MQCL cutting conditions

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TLDR
In this article, a parametric and nonparametric description of surface topography after turning in the dry and MQCL conditions is presented, with the application of the Infinite Focus G4 microscope.
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This article is published in Measurement.The article was published on 2018-06-01. It has received 134 citations till now. The article focuses on the topics: Surface roughness.

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Nano-enhanced biolubricant in sustainable manufacturing: From processability to mechanisms

TL;DR: In this paper , a comprehensive quantitative assessment of processability based on tribological, thermal, and machined surface quality aspects for nano-enhanced biolubricant (NEBL) application in turning, milling, and grinding is presented.
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Milling force and surface morphology of 45 steel under different Al2O3 nanofluid concentrations

TL;DR: In this article, the effects of cottonseed oil-based Al2O3 nanofluid concentrations on the milling force and workpiece surface quality were investigated using 45 steel milling experiments.
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Optimization and Analysis of Surface Roughness, Flank Wear and 5 Different Sensorial Data via Tool Condition Monitoring System in Turning of AISI 5140.

TL;DR: This study investigates the optimization of five different sensorial criteria, additional to tool wear (VB) and surface roughness (Ra), via the Tool Condition Monitoring System (TCMS) for the first time in the open literature.
References
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Journal ArticleDOI

A study on droplets sizes, their distribution and heat exchange for minimum quantity cooling lubrication (MQCL)

TL;DR: In this paper, the influence of emulsion mist formation parameters and the nozzle distance from the tool-chip interface, on the droplet velocity at the nozzle outlet, on active medium atomization angle as well as on the diameter and number of droplets supplied to the cutting zone was analyzed.
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Prediction of surface roughness in hard turning under high pressure coolant using Artificial Neural Network

TL;DR: In this article, an ANN based predictive model of surface roughness in turning hardened EN 24T steel has been presented by using Neural Network Tool Box 7 of MATLAB R2015a for different levels of cutting speed, feed rate, material hardness and cutting conditions.
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Predicting tool life in turning operations using neural networks and image processing

TL;DR: Although the complete-automated solution, Neural Wear software for tool wear recognition plus the ANN model of tool life prediction, presented a slightly higher error than the direct measurements, it was within the same range and can meet all industrial requirements.
Journal ArticleDOI

Tool wear characterizations in finish turning of AISI 1045 carbon steel for MQCL conditions

TL;DR: In this paper, an analysis of tool wear of P25 cemented carbide inserts in finish turning of AISI 1045 carbon steel for different cooling conditions: dry cutting, minimum quantity cooling-lubrication (MQCL) and MQCL with phosphate ester-based EP/AW additive is presented.
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Dry cutting effect in turning of a duplex stainless steel as a key factor in clean production

TL;DR: In this paper, a study was conducted to identify the optimal machining strategy and conditions, which will lead to the reduction of pollution generated by cooling/lubricating with coolants and emulsions, as well as reduce energy consumption during manufacturing process.
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