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Development of process performance simulator (PPS) and parametric optimization for sustainable machining considering carbon emission, cost and energy aspects

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  • Khan, A.M.
  • Liang, L.
  • Mia, M.
  • Gupta, M.K.
  • Wei, Z.
  • Jamil, M.
  • Ning, H.

Abstract

The manufacturing industries consume one-third of global energy. Intensive use of electrical energy in industries provides the researchers and experts strong reasons to develop and propose strategies to minimize energy consumption. Evidently, the advanced technologies such as nanofluid minimum quantity lubrication in machining and process optimization accompanied by holistic models can eliminate the use of conventional fluids to reduce production cost and to cope up with environmental issues of global warming and climate change. This study investigates the holistic analysis of four metrics, i.e., surface quality, energy, cost, and carbon emission that influence the impact of the machining process on the environment of China. Al2O3 based nanofluid was prepared and used in the external turning of Haynes 25 alloys to improve the machining and to promote sustainability. Multi-objective optimization was performed to find out a trade-off relation for product quality, energy consumption and production cost. Results showed that the minimum levels of energy consumption and carbon emission were obtained at the high levels of feed rate and cutting speed. The Carbon Emission Factors (CEF) of used resources have the most significant effects on CO2 emissions. Furthermore, the feed rate was found to be the most significant parameter on the machining performance indices. The application of nanoparticles helped to reduce the cutting energy and CO2 emission, which are proportional to electricity consumption. A holistic component activity-based cost model was developed, and it was noted that the overhead and workpiece cost shared more than 95% of the total cost. Multi-objective optimization reduced specific energy by 18.10%, carbon emission by 22.17% and product cost by 16.25%. Moreover, the present study deals with 3E, i.e., Energy, Environment, and Economy. The optimum cutting parameters obtained from the concept of 3E at the machine shop level can significantly improve efficiency of nanofluid MQL assisted machining (NFMQL) process, reduce cost per unit of product, and achieve the low carbon manufacturing goal.

Suggested Citation

  • Khan, A.M. & Liang, L. & Mia, M. & Gupta, M.K. & Wei, Z. & Jamil, M. & Ning, H., 2021. "Development of process performance simulator (PPS) and parametric optimization for sustainable machining considering carbon emission, cost and energy aspects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
  • Handle: RePEc:eee:rensus:v:139:y:2021:i:c:s1364032121000344
    DOI: 10.1016/j.rser.2021.110738
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    References listed on IDEAS

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    1. Yoon, Hae-Sung & Kim, Eun-Seob & Kim, Min-Soo & Lee, Jang-Yeob & Lee, Gyu-Bong & Ahn, Sung-Hoon, 2015. "Towards greener machine tools – A review on energy saving strategies and technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 870-891.
    2. Aqib Mashood Khan & Muhammad Jamil & Konstantinos Salonitis & Shoaib Sarfraz & Wei Zhao & Ning He & Mozammel Mia & GuoLong Zhao, 2019. "Multi-Objective Optimization of Energy Consumption and Surface Quality in Nanofluid SQCL Assisted Face Milling," Energies, MDPI, vol. 12(4), pages 1-22, February.
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    4. Raja, M. & Vijayan, R. & Dineshkumar, P. & Venkatesan, M., 2016. "Review on nanofluids characterization, heat transfer characteristics and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 163-173.
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    Cited by:

    1. Wang, Jinling & Tian, Yebing & Hu, Xintao & Han, Jinguo & Liu, Bing, 2023. "Integrated assessment and optimization of dual environment and production drivers in grinding," Energy, Elsevier, vol. 272(C).
    2. Shuhong Wang & Xiaojing Yi, 2023. "Can the Financial Industry ‘Anchor’ Carbon Emission Reductions?— The Mediating and Moderating Effects of the Technology Market," Energy & Environment, , vol. 34(3), pages 533-559, May.
    3. Md. Rezaul Karim & Juairiya Binte Tariq & Shah Murtoza Morshed & Sabbir Hossain Shawon & Abir Hasan & Chander Prakash & Sunpreet Singh & Raman Kumar & Yadaiah Nirsanametla & Catalin I. Pruncu, 2021. "Environmental, Economical and Technological Analysis of MQL-Assisted Machining of Al-Mg-Zr Alloy Using PCD Tool," Sustainability, MDPI, vol. 13(13), pages 1-22, June.

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