A comprehensive exploration of minimum quantity lubrication in machining process

Minimal Quantity Lubrication (MQL) has received a lot of interest in the machining processes because of its potential and environmental benefits. Transitioning from traditional flood cooling technologies to MQL has various advantages, including lower heat generation and better chip evacuation. The MQL approach has shown to be effective since it conforms with “green machining” criteria. The current study reviews significant research publications on the usage of cutting fluids and fluids based on nanofluids, as well as mineral and vegetable oils for various machining operations, including drilling, turning, milling and grinding. The suitability of the MQL technique has been demonstrated as it aligns with the requirements of environmentally friendly machining. The paper elucidates the mechanism behind the MQL technique and systematically explores its impact on the performance parameters of diverse machining processes. The study gives a detailed investigation of MQL in terms of its impact on cutting performance, tool life, and surface finish. Numerous experimental studies indicate that employing MQL results in surface quality superior to dry machining and comparable to that achieved with wet machining. Furthermore, the application of MQL reduces cutting forces, cutting zone temperature, tool wear, and friction coefficient when compared to both dry and wet machining. Consequently, the MQL technique has demonstrated its viability as a feasible alternative to flood lubrication under similar performance parameters.

Authors

Institutions

Publication Details

Journal
JOURNAL OF MECHANICAL ENGINEERING AND SCIENCES
Published
2025-03-30
DOI
https://doi.org/10.15282/jmes.19.1.2025.1.0818
Citations
2
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
1.43

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A comprehensive exploration of minimum quantity lubrication in machining process

Mohammad Arif Parray, A. Gulzar, M. Javed Khan, Aqib Fayaz
2 citations
JOURNAL OF MECHANICAL ENGINEERING AND SCIENCES
Advanced machining processes and optimization
1.43
article

A comprehensive exploration of minimum quantity lubrication in machining process

Mohammad Arif Parray, A. Gulzar, M. Javed Khan, Aqib Fayaz
article en
2 citations

Abstract

Minimal Quantity Lubrication (MQL) has received a lot of interest in the machining processes because of its potential and environmental benefits. Transitioning from traditional flood cooling technologies to MQL has various advantages, including lower heat generation and better chip evacuation. The MQL approach has shown to be effective since it conforms with “green machining” criteria. The current study reviews significant research publications on the usage of cutting fluids and fluids based on nanofluids, as well as mineral and vegetable oils for various machining operations, including drilling, turning, milling and grinding. The suitability of the MQL technique has been demonstrated as it aligns with the requirements of environmentally friendly machining. The paper elucidates the mechanism behind the MQL technique and systematically explores its impact on the performance parameters of diverse machining processes. The study gives a detailed investigation of MQL in terms of its impact on cutting performance, tool life, and surface finish. Numerous experimental studies indicate that employing MQL results in surface quality superior to dry machining and comparable to that achieved with wet machining. Furthermore, the application of MQL reduces cutting forces, cutting zone temperature, tool wear, and friction coefficient when compared to both dry and wet machining. Consequently, the MQL technique has demonstrated its viability as a feasible alternative to flood lubrication under similar performance parameters.

JOURNAL OF MECHANICAL ENGINEERING AND SCIENCES
Indian Institute of Technology Jammu (IN), Islamic University of Science and Technology (IN), National Institute of Technology Srinagar (IN)
National Institute of Technology Srinagar
Openalex Percentile: Top 21%
Advanced machining processes and optimization
1.43
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.