<sub>Synthesis, Characterization, and Application of Nanoparticle Doped Oil Based Cutting Fluid in Machining of Low Carbon Steel</sub>
Low carbon steel is extensively used in various industries due to its excellent weldability, ductility, and cost-effectiveness. Despite these advantages, achieving superior surface quality during machining remains a significant concern, especially under conventional lubrication conditions. In pursuit of a sustainable and efficient solution, this study investigates the performance of a novel bio-based cutting fluid derived from Putranjiva roxburghii seed oil, extracted through a natural process from seeds collected manually. To further enhance the fluid’s lubrication and heat dissipation properties, magnesium oxide (MgO) nanoparticles were dispersed into the oil using magnetic stirring, a method effective in preventing agglomeration and ensuring uniform nanoparticle distribution.The machining experiments involved facing operations on low carbon steel using a GD lathe machine, conducted under two conditions: one using the MgO-doped cutting fluid and the other under dry (no cutting fluid) conditions. Trials were performed at multiple spindle speeds (RPMs) to evaluate the combined effect of lubrication and cutting speed on machining performance. Post-machining, the samples were subjected to surface structure analysis to assess variations in surface integrity and quality resulting from different test conditions.This study demonstrates that the use of MgO nanoparticle-enhanced Putranjiva oil significantly improves the surface finish and overall quality of the machined surface compared to dry machining. The results support the potential of bio-based nanofluids as an environmentally friendly alternative to conventional cutting fluids, particularly for improving machinability and sustainability in metal cutting applications.
Publication Details
- Journal
- Figshare
- Published
- 2025-01-01
- DOI
- https://doi.org/10.6084/m9.figshare.29648915.v1
- Primary Topic
- Advanced machining processes and optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00