What question did this study set out to answer?

The study aims to evaluate the machining performance of hardened AISI 4140 steel under different lubrication methods.

Multi-response optimization of machining performance and energy efficiency in sustainable Nanofluid-MQL face milling of hardened AISI 4140 steel

View Full Paper

Ask AI

Bookmark

Randomized trial evaluates machining performance in hardened steel using nanofluid-assisted MQL, indicating superior efficiency.

The study aims to evaluate the machining performance of hardened AISI 4140 steel under different lubrication methods.
Experimental evaluation of face milling under dry cutting, MQL, and nanofluid-MQL conditions.
Analysis of parameters like cutting speed and feed rate on various performance metrics.
Optimization using SWARA–CoCoSo to determine optimal cutting conditions.
Nanofluid-MQL achieved the lowest surface roughness (Ra) value of 0.090 µm, compared to 0.423 µm under dry cutting.
Nanofluid-MQL reduced cutting temperature by up to 12.62% and power consumption by 7.03% compared to dry machining.
Optimal conditions identified at a cutting speed of 90 m/min and feed rate of 0.05 mm/tooth using nanofluid-MQL.

A 2026 study studied this question.

View Full Paper

Ask AI

Bookmark