Advancing sustainable machining of inconel 718 through nanoparticle-enhanced coconut oil and RSM–GA optimization

Motivated by the growing imperative for greener and more sustainable machining practices, this investigation evaluates the potential of eco-benign lubricants to mitigate frictional interactions at the tool–workpiece interface. Particular attention is directed toward nanofluids derived from vegetable oils, which are examined as viable and environmentally responsible substitutes for conventional metalworking fluids. In the present study, coconut oil was systematically enhanced by dispersing alumina and silica nanoparticles in the range of 0–1.4%, after which the prepared nanofluid samples were thoroughly examined using spectroscopic techniques to determine the formulation with the highest dispersion stability. Hard milling trials on Inconel 718 were then carried out under four distinct lubrication environments: dry cutting, pure coconut oil, coconut oil enriched with 0.8% alumina nanoparticles, and coconut oil containing 0.8% silica nanoparticles. Among these conditions, the alumina-based nanofluid delivered the most pronounced improvements, achieving decreases of 43.089% in surface roughness, 27.397% in cutting force, 23.437% in cutting temperature, and 45.833% in tool wear relative to dry machining. Capitalizing on the superior capability of this nanofluid, a Taguchi L27 experimental framework was subsequently executed under the optimal lubrication condition, and the resulting data were further optimized using a Genetic Algorithm to determine the best combination of machining parameters. Experimental confirmation of the optimized parameters showed strong alignment with model predictions, with the average deviation limited to just 2.6%. Overall, the findings clearly demonstrate that nanoparticle-infused bio-lubricants substantially enhance machining performance, extend tool longevity, and offer a promising pathway toward more sustainable manufacturing practices.

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Publication Details

Journal
Scientific Reports
Published
2026-03-31
DOI
https://doi.org/10.1038/s41598-026-46713-5
Primary Topic
Advanced machining processes and optimization
Type
article
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article

Advancing sustainable machining of inconel 718 through nanoparticle-enhanced coconut oil and RSM–GA optimization

Sikata Samantaray, Omar Almomani, Ripendeep Singh, Vipulsinh Rajput et al.
Scientific Reports
Advanced machining processes and optimization
article

Advancing sustainable machining of inconel 718 through nanoparticle-enhanced coconut oil and RSM–GA optimization

Sikata Samantaray, Omar Almomani, Ripendeep Singh, Vipulsinh Rajput, Nagaraj Patil, A. C. Umamaheshwer Rao, Mohit Sahani, Lema Abate, B. Vishnu Vardhana Naidu, Abhijit Bhowmik
article en

Abstract

Motivated by the growing imperative for greener and more sustainable machining practices, this investigation evaluates the potential of eco-benign lubricants to mitigate frictional interactions at the tool–workpiece interface. Particular attention is directed toward nanofluids derived from vegetable oils, which are examined as viable and environmentally responsible substitutes for conventional metalworking fluids. In the present study, coconut oil was systematically enhanced by dispersing alumina and silica nanoparticles in the range of 0–1.4%, after which the prepared nanofluid samples were thoroughly examined using spectroscopic techniques to determine the formulation with the highest dispersion stability. Hard milling trials on Inconel 718 were then carried out under four distinct lubrication environments: dry cutting, pure coconut oil, coconut oil enriched with 0.8% alumina nanoparticles, and coconut oil containing 0.8% silica nanoparticles. Among these conditions, the alumina-based nanofluid delivered the most pronounced improvements, achieving decreases of 43.089% in surface roughness, 27.397% in cutting force, 23.437% in cutting temperature, and 45.833% in tool wear relative to dry machining. Capitalizing on the superior capability of this nanofluid, a Taguchi L27 experimental framework was subsequently executed under the optimal lubrication condition, and the resulting data were further optimized using a Genetic Algorithm to determine the best combination of machining parameters. Experimental confirmation of the optimized parameters showed strong alignment with model predictions, with the average deviation limited to just 2.6%. Overall, the findings clearly demonstrate that nanoparticle-infused bio-lubricants substantially enhance machining performance, extend tool longevity, and offer a promising pathway toward more sustainable manufacturing practices.

Scientific Reports
Chandigarh University (IN), Al-Ahliyya Amman University (JO), Jain University (IN), Siksha O Anusandhan University (IN), Mizan Tepi University (ET), General Motors (India) (IN), Chitkara University (IN), Sharda University (IN), Saveetha University (IN)
Responsible consumption and production
Openalex Percentile: Top 7%
Advanced machining processes and optimization
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