Volume 5, 2018
|Number of page(s)
|01 June 2018
Prediction of surface roughness and cutting force under MQL turning of AISI 4340 with nano fluid by using response surface methodology
Bharati Vidyapeeth College of Engineering,
2 Department of Mechanical Engineering, Sanjay Ghodawat Group of Institutions, College of Engineering, Atigre M.S, Kolhapur, India
* e-mail: firstname.lastname@example.org
Accepted: 18 January 2018
This paper presents an investigation into the minimum quantity lubrication mode with nano fluid during turning of alloy steel AISI 4340 work piece material with the objective of experimental model in order to predict surface roughness and cutting force and analyze effect of process parameters on machinability. Full factorial design matrix was used for experimental plan. According to design of experiment surface roughness and cutting force were measured. The relationship between the response variables and the process parameters is determined through the response surface methodology, using a quadratic regression model. Results show how much surface roughness is mainly influenced by feed rate and cutting speed. The depth of cut exhibits maximum influence on cutting force components as compared to the feed rate and cutting speed. The values predicted from the model and experimental values are very close to each other.
Key words: MQL / nano fluid / surface roughness / cutting force / RSM
© P.B. Patole and V.V. Kulkarni, Published by EDP Sciences 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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