Hybrid Nanofluid-MQL and Cold Air Cooling for Hard Milling: RSM–PSO Multi-response Optimization

https://doi.org/10.5614/j.eng.technol.sci.2026.58.5.6

Authors

  • The Vinh Do Faculty of Mechanical Engineering, Thai Nguyen University of Technology, 666 3/2 Street, Tich Luong Ward, Thai Nguyen Province 24131,
  • Nguyen Anh Vu Le Faculty of Mechanical Engineering, Nha Trang University, 02 Nguyen Dinh Chieu Street, Bac Nha Trang Ward, Khanh Hoa Province, 57134 https://orcid.org/0000-0002-8744-3909
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Abstract

This study investigates a hybrid cooling–lubrication approach combining nanofluid-assisted minimum quantity lubrication (MQL) with cold-air cooling in the hard milling of SKD11 steel, aiming to improve both surface quality and productivity. Response surface methodology (RSM) was employed to model the relationships between machining parameters and two key performance indicators, namely surface roughness (Ra) and material removal rate (MRR). The developed models were integrated with particle swarm optimization (PSO) for multi-objective optimization. Compared with conventional MQL, the hybrid approach reduced Ra by approximately 5–10% under similar cutting conditions, indicating enhanced cooling and lubrication performance. The optimization results revealed distinct trade-offs between surface quality and productivity. When surface quality was prioritized (wRa = 0.7), a minimum Ra of 0.160 µm was achieved with a relatively low MRR of about 653 mm³/min. In contrast, both the balanced (wRa = 0.5) and productivity-oriented (wRa = 0.3) scenarios converged to the same optimal solution (Ra ≈ 0.245 µm, MRR ≈ 1790 mm³/min). This convergence suggests that MRR dominates the optimization when its weighting is comparable to or higher than that of Ra, indicating a plateau region on the trade-off surface. The proposed RSM–PSO framework provides both an effective optimization approach and new insight into balancing surface integrity and productivity in hybrid-cooled hard milling

How to Cite

The Vinh Do, Nguyen Anh Vu Le (2026). Hybrid Nanofluid-MQL and Cold Air Cooling for Hard Milling: RSM–PSO Multi-response Optimization. Journal of Engineering and Technological Sciences, Vol. 58 No. 5 (2026): Vol. 58 No. 5(2026): October, 673-684. https://doi.org/10.5614/j.eng.technol.sci.2026.58.5.6

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Date Log

Submitted
September 27, 2025
Accepted
July 22, 2026
Published
August 15, 2026

Keywords

  • cold air cooling
  • hard milling
  • nanofluid MQL
  • PSO
  • RSM
  • SKD11

Issue

Vol. 58 No. 5 (2026): Vol. 58 No. 5(2026): October

Section

Articles

How to Cite

Hybrid Nanofluid-MQL and Cold Air Cooling for Hard Milling: RSM–PSO Multi-response Optimization. (2026). Journal of Engineering and Technological Sciences, 58(5), 673-684. https://doi.org/10.5614/j.eng.technol.sci.2026.58.5.6

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