Optimization of Multiple Roughness Characteristics for Turning of AISI 1040 Steel under Different Cutting Conditions

Haque, Tanveer; Kumar, Shubham; Upadhaya, Devjyoti; Barman, Manik; Mukhopadhyay, Arkadeb

doi:10.18052/www.scipress.com/IJET.10.1

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Optimization of Multiple Roughness Characteristics for Turning of AISI 1040 Steel under Different Cutting Conditions

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Abstract:

The present work aims to optimize multiple roughness characteristics i.e. centre line average, root mean square and mean line peak spacing roughness parameters for AISI 1040 medium carbon steel for turning operation. The turning parameters considered are feed rate, depth of cut and cutting condition and are varied at three different levels. Since the present investigation considers three process parameters at three different levels, the combinations laid down in Taguchi’s L₉ orthogonal array is employed to carry out the experiments. Grey relational analysis is used for the optimization. Optimal surface roughness is achieved for a depth of cut of 0.4 mm, feed rate of 0.07 mm/rev and under water cooled cutting condition. Analysis of variance revealed the highest contribution from feed rate in controlling the surface roughness.

Info:

Periodical:

International Journal of Engineering and Technologies (Volume 10)

Pages:

1-10

DOI:

https://doi.org/10.18052/www.scipress.com/IJET.10.1

Citation:

T. Haque et al., "Optimization of Multiple Roughness Characteristics for Turning of AISI 1040 Steel under Different Cutting Conditions", International Journal of Engineering and Technologies, Vol. 10, pp. 1-10, 2017

Online since:

March 2017

Authors:

Tanveer Haque, Shubham Kumar, Devjyoti Upadhaya, Manik Barman, Arkadeb Mukhopadhyay

Keywords:

AISI 1040 Steel, ANOVA, Grey Relational Analysis, Optimization, Turning

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Open Access

This work is licensed under a
Creative Commons Attribution 4.0 International License

References:

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Cited By:

[1] A. Mukhopadhyay, M. Barman, P. Sahoo, "Optimization of Fractal Dimension of Turned AISI 1040 Steel Surface Considering Different Cutting Conditions", International Journal of Surface Engineering and Interdisciplinary Materials Science, Vol. 7, p. 19, 2019

DOI: https://doi.org/10.4018/IJSEIMS.2019070102

[2] A. Al-Shayea, F. Abdullah, M. Noman, H. Kaid, E. Abouel Nasr, "Studying and Optimizing the Effect of Process Parameters on Machining Vibration in Turning Process of AISI 1040 Steel", Advances in Materials Science and Engineering, Vol. 2020, p. 1, 2020

DOI: https://doi.org/10.1155/2020/5480614

[3] D. Vukelic, K. Simunovic, Z. Kanovic, T. Saric, B. Tadic, G. Simunovic, "Multi-objective optimization of steel AISI 1040 dry turning using genetic algorithm", Neural Computing and Applications, 2021

DOI: https://doi.org/10.1007/s00521-021-05877-z