Influence of Various Cutting Fluids on Energy Consumption during Turning

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In this paper an experiment was carried out to examine the magnitude of differences among cutting fluids and their influence on lathe power consumption during machining. It was discovered that there is no universal cutting fluid. An attempt was made to study the possibility of Artificial Neural Network to model the behavior function for all cutting fluids. This could be used as a foundation for later database building where it would be possible to predict how certain cutting fluid will behave in a specific machining parameter combination.

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252-256

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February 2016

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© 2016 Trans Tech Publications Ltd. All Rights Reserved

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[1] M. Jedinak, Energy assessment of the impact of cutting fluid for machining process, Slovak University of Technology in Bratislava, Faculty of Mechanical Engineering, Bartislava, (2013).

Google Scholar

[2] M. Bachraty, M. Tolnay, M. Jedinak, M. Durana, J. Slamka, O. Stas, Impact of cutting environment on cutting power in selected conditions, Advanced Manufacturing Technologies: 6th international seminar. Sozopol /Bulgaria/, 22-28 June 2012, Sofia (2012).

Google Scholar

[3] L. De Chiffe, W. Belluco, Comparison of methods for cutting fluid performance testing, CIRP Annals – Manufacturing Technology 49 (2000) 57-60.

DOI: 10.1016/s0007-8506(07)62895-9

Google Scholar

[4] O. Cakir, A. Yardimeden, T. Ozben, E. Kilickap, Selection of cutting fluids in machining processes, Journal of Achievements in Materials and manufacturing Engineering 25 (2007) 99-102.

Google Scholar

[5] S. Khandekar, M. Ravi Sankar, V. Agnihotri, J. Ramkumar, Nano-cutting fluid for enhancement of metal cutting performance, materials and Manufacturing Processes 27 (2012) 963-967.

DOI: 10.1080/10426914.2011.610078

Google Scholar

[6] P. Kovac, M. Rodic, V. Pucovsky, B. Savkovic, M. Gostimirovic, Multi-output fuzzy inference system for modeling cutting temperature and tool life in face milling, Journal of Mechanical Science and Technology 28 (2014) 4247-4256.

DOI: 10.1007/s12206-014-0938-0

Google Scholar