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Sustainable machining. Modeling and optimization of temperature and surface roughness in the milling of AISI D2 steel

Aqib Mashood Khan (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Muhammad Jamil (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Ahsan Ul Haq (Industrial Engineering Department, University of Engineering and Technology Taxila, Taxila, Pakistan)
Salman Hussain (Industrial Engineering Department, University of Engineering and Technology Taxila, Taxila, Pakistan)
Longhui Meng (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Ning He (College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China)

Industrial Lubrication and Tribology

ISSN: 0036-8792

Article publication date: 10 December 2018

Issue publication date: 5 March 2019

277

Abstract

Purpose

Sustainable machining is a global consensus and the necessity to cope up the serious environmental threats. Minimum quantity lubrication (MQL) and nanofluids-based MQL(NFMQL) are state-of-the-art sustainable lubrication modes. The purpose of this study is to investigate the effect of process parameters, such as feed rate, depth of cut and cutting fluid flow rate, on temperature and surface roughness of the manufactured pieces during face milling of the AISI D2 steel.

Design/methodology/approach

A statistical technique called response surface methodology with Box–Behnken Design was used to design experimental runs, and empirical modeling was presented. Analysis of variance was carried out to evaluate the model’s accuracy and the validation of the applied technique.

Findings

A comprehensive analysis revealed the superiority of implementing NFMQL in comparison to MQL within the levels of process parameters. The comparison has shown a significant reduction of temperature under NFMQL at the tool-workpiece interface from 16.2 to 34.5 per cent and surface roughness from 11.3 to 12 per cent.

Practical implications

This research is useful for practitioners to predict the responses in workshop and select appropriate cutting parameters. Moreover, this research will be helpful to reduce the resource which will ultimately save energy consumption and cost.

Originality/value

To cope with the industrial challenges and tribological issues associated with the milling of AISI D2 steel, experiments were conducted in a distinct machining mode with innovative cooling/lubrication. Until now, few studies have addressed the key lubrication effects of Al2O3-based nanofluid on the machinability of D2 steel under NFMQL lubrication condition.

Keywords

Acknowledgements

The authors are very grateful to Dr Andrea Mueller (specialist for academic writing in Nanjing University of Aeronautics and Astronautics NUAA) and Dr Conni Postelli (American English teacher in NUAA) for improving the language of the manuscript.

Citation

Khan, A.M., Jamil, M., Ul Haq, A., Hussain, S., Meng, L. and He, N. (2019), "Sustainable machining. Modeling and optimization of temperature and surface roughness in the milling of AISI D2 steel", Industrial Lubrication and Tribology, Vol. 71 No. 2, pp. 267-277. https://doi.org/10.1108/ILT-11-2017-0322

Publisher

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Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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