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Lubricants
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Minimum Quantity Lubrication (MQL): Advances, Applications, and Future Perspectives
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Minimum Quantity Lubrication (MQL): Advances, Applications, and Future Perspectives

A special issue of Lubricants (ISSN 2075-4442).

Deadline for manuscript submissions: 30 November 2026 | Viewed by 12387

Editors

Prof. Dr. Songmei Yuan

E-Mail Website
Guest Editor
School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China
Interests: minimum quantity lubrication (MQL); ultrasonic drive technology; advanced processing technology and equipment; cutting tools; tool wear
Prof. Dr. Lutao Yan

E-Mail Website
Guest Editor
School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: continuous minimum quantity lubrication; visual classification for robot picking; coal and gangue recognition; robot-assisted surgery; tribological behavior

Special Issue Information

Dear Colleagues,

Minimum quantity lubrication (MQL) has been widely used during cutting of various materials. Nevertheless, according to recent reports, MQL significantly improves the working environment, reduces pollution to the natural environment, and represents an efficient and low-carbon machining technology that aligns with the principles of clean production.

In this Special Issue, titled “Minimum Quantity Lubrication (MQL): Advances, Applications, and Future Perspectives”, we are looking for outstanding research community possesing experimental and theoretical results with a special focus on the influence of MQL treatment, cooling and lubrication mechanisms, interfacial contact modelling, systems, applications, and the future development of MQL. Original papers are invited on topics such as novel minimum cooling/lubrication conditions, nano-enhanced cryogenic/biolubricant in MQL manufacturing, optimization of technological parameters under MQL, design of cryogenic/MQL systems, friction modelling in metal cutting, and applications of MQL techniques in different manufacturing processes. Moreover, review papers on recent developments and future perspectives regarding MQL are also welcome.

We look forward to your contributions.

Prof. Dr. Songmei Yuan
Prof. Dr. Lutao Yan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Lubricants is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • minimum quantity lubrication (MQL)
  • friction and wear
  • tool wear
  • advanced lubrication technologies

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Published Papers (6 papers)

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Research

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30 pages, 41827 KB  
Article
A Novel Assessment Model for the Sustainability of Clean Cutting Technology Based on Game Theory
by Zewen Li, Wei Zhao, Junjie Hu, Peng Zhao, Liang Li and Feng Kong
Lubricants 2026, 14(2), 89; https://doi.org/10.3390/lubricants14020089 - 14 Feb 2026
Viewed by 779
Abstract
To enhance the sustainability of manufacturing, various clean cutting technologies have been developed, yet their sustainability assessment faces challenges in balancing multiple conflicting objectives and stakeholder interests. This paper proposes a game theory-based evaluation framework that treats environmental, technical, economic, and social dimensions [...] Read more.
To enhance the sustainability of manufacturing, various clean cutting technologies have been developed, yet their sustainability assessment faces challenges in balancing multiple conflicting objectives and stakeholder interests. This paper proposes a game theory-based evaluation framework that treats environmental, technical, economic, and social dimensions as cooperative players. The Nash equilibrium model is employed to dynamically reconcile subjective weights from the analytic hierarchy process and objective weights from the entropy method, thus achieving optimal weight allocation. Experimental studies on Ti-6Al-4V titanium alloy milling compared dry milling, minimum quantity lubrication, and cryogenic minimum quantity lubrication (CMQL) under different parameters. Results demonstrate that the game-theoretic model effectively integrates preferences and achieves Nash equilibrium. CMQL showed superior performance, increasing tool life by approximately 40% and reducing surface roughness by about 25% compared to dry milling. Coated inserts reduced carbon emissions by nearly 30% versus end mills. The Nash equilibrium analysis demonstrates that dry milling with coated inserts attains the highest level of processing sustainability under high-speed conditions due to synergistic environmental and economic advantages, while simultaneously revealing practical trade-offs among competing objectives. This study confirms that the proposed framework enables scientific weight coordination and provides a quantifiable, interpretable decision-making system for sustainable process selection. Full article
(This article belongs to the Special Issue Minimum Quantity Lubrication (MQL): Advances, Applications, and Future Perspectives)
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25 pages, 3515 KB  
Article
Optimizing Sustainable Machining Conditions for Incoloy 800HT Using Twin-Nozzle MQL with Bio-Based Groundnut Oil Lubrication
by Ramai Ranjan Panigrahi, Ramanuj Kumar, Ashok Kumar Sahoo and Amlana Panda
Lubricants 2025, 13(8), 320; https://doi.org/10.3390/lubricants13080320 - 23 Jul 2025
Cited by 5 | Viewed by 2720
Abstract
This study explores the machinability of Incoloy 800HT (high temperature) under a sustainable lubrication approach, employing a twin-nozzle minimum quantity lubrication (MQL) system with groundnut oil as a green cutting fluid. The evaluation focuses on key performance indicators, including surface roughness, tool flank [...] Read more.
This study explores the machinability of Incoloy 800HT (high temperature) under a sustainable lubrication approach, employing a twin-nozzle minimum quantity lubrication (MQL) system with groundnut oil as a green cutting fluid. The evaluation focuses on key performance indicators, including surface roughness, tool flank wear, power consumption, carbon emissions, and chip morphology. Groundnut oil, a biodegradable and nontoxic lubricant, was chosen to enhance environmental compatibility while maintaining effective cutting performance. The Taguchi L16 orthogonal array (three factors and four levels) was utilized to conduct experimental trials to analyze machining characteristics. The best surface quality (surface roughness, Ra = 0.514 µm) was obtained at the lowest depth of cut (0.2 mm), modest feed (0.1 mm/rev), and moderate cutting speed (160 m/min). The higher ranges of flank wear are found under higher cutting speed conditions (320 and 240 m/min), while lower wear values (<0.09 mm) were observed under lower speed conditions (80 and 160 m/min). An entropy-integrated multi-response optimization using the MOORA (multi-objective optimization based on ratio analysis) method was employed to identify optimal machining parameters, considering the trade-offs among multiple conflicting objectives. The entropy method was used to assign weights to each response. The obtained optimal conditions are as follows: cutting speed = 160 m/min, feed = 0.1 mm/rev, and depth of cut = 0.2 mm. Optimized outcomes suggest that this green machining strategy offers a viable alternative for sustainable manufacturing of difficult-to-machine alloys like Incoloy 800 HT. Full article
(This article belongs to the Special Issue Minimum Quantity Lubrication (MQL): Advances, Applications, and Future Perspectives)
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Review

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30 pages, 2329 KB  
Review
Cutting Tool Wear Minimization in Machining Operations: A Review
by Mohsen Soori
Lubricants 2026, 14(8), 300; https://doi.org/10.3390/lubricants14080300 - 1 Aug 2026
Viewed by 519
Abstract
Cutting tool wear significantly influences machining performance, surface quality, and manufacturing cost. Proper minimization of cutting tool wear will result in enhanced life of the cutting tool, surface integrity, precision, and sustainability of the machining process. There are various methods for minimizing cutting [...] Read more.
Cutting tool wear significantly influences machining performance, surface quality, and manufacturing cost. Proper minimization of cutting tool wear will result in enhanced life of the cutting tool, surface integrity, precision, and sustainability of the machining process. There are various methods for minimizing cutting tool wear in machining operations. These include the optimization of parameters such as reducing the feed and speed, use of proper coating such as TiN and Al2O3, lubrication/cooling, and proper material for the cutting tool like carbide and ceramic materials. The application of chip breakers and high machine rigidity can minimize wear by lowering heat and friction, which are the major causes of wear. Reduction in wear will ensure a better surface finish, enhanced tool life, and economic efficiency of the machining process. The main objective of this research paper is to conduct an extensive study on wear of cutting tools in machining operations. As a result, the study discusses several advanced methods of tool wear detection in cutting tools, including sensor-based methods, machine vision, and AI/ML-assisted predictive maintenance. Additionally, a critical assessment in tool wear minimization is conducted to apply new material to the cutting tool, the coating process, cutting parameter and path optimization, cooling and lubrication systems such as minimum amount lubrication and cryogenic cooling. Moreover, various challenges with intelligent and autonomous manufacturing systems that arise in tool wear prediction with regard to availability of data and reliability of prediction models are discussed in the study. Finally, potential future research directions are provided, with an emphasis on the importance of using digital twin technologies and sustainable manufacturing approaches in tool wear management. Full article
(This article belongs to the Special Issue Minimum Quantity Lubrication (MQL): Advances, Applications, and Future Perspectives)
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34 pages, 2262 KB  
Review
The Role of Machine Learning in Minimum Quantity Lubrication for Sustainable Machining: A Review
by Uma Maheshwera Reddy Paturi, Mohammed Muttahir, Satrio Herbirowo and Nagireddy Gari Subba Reddy
Lubricants 2026, 14(7), 265; https://doi.org/10.3390/lubricants14070265 - 6 Jul 2026
Viewed by 871
Abstract
Sustainable machining is gaining attention in modern manufacturing due to its cleaner operations, improved resource utilization, and reduced environmental impact. Among sustainable machining methods, minimum quantity lubrication (MQL) successfully minimizes cutting fluid consumption while maintaining adequate cooling and lubrication. This review examines recent [...] Read more.
Sustainable machining is gaining attention in modern manufacturing due to its cleaner operations, improved resource utilization, and reduced environmental impact. Among sustainable machining methods, minimum quantity lubrication (MQL) successfully minimizes cutting fluid consumption while maintaining adequate cooling and lubrication. This review examines recent developments and future directions in MQL-assisted machining, with particular emphasis on machine learning (ML)-based modeling and optimization techniques. A systematic review comprising literature identification, screening, scientometric analysis, and critical evaluation was employed to analyze 120 papers published mainly between 2010 and 2026. The reviewed studies employed ML models such as artificial neural networks, support vector machines, random forests, gradient boosting, and hybrid optimization approaches to predict machinability parameters, including surface roughness, tool wear, cutting force, cutting temperature, energy consumption, and chip morphology. The findings indicate that ML-assisted MQL processes improve prediction accuracy, machining efficiency, process monitoring, and sustainability performance by reducing energy consumption, minimizing cutting fluid usage, and improving machining quality. The analysis also identifies key research gaps and prospects for intelligent and sustainable machining. Full article
(This article belongs to the Special Issue Minimum Quantity Lubrication (MQL): Advances, Applications, and Future Perspectives)
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32 pages, 10460 KB  
Review
A Review of Nanofluid Minimum Quantity Lubrication Technology Applications in Various Machining Processes
by Tai Ma, Jie Yang, Jielin Chen, Jiaqiang Dang, Qinglong An and Ming Chen
Lubricants 2026, 14(3), 103; https://doi.org/10.3390/lubricants14030103 - 27 Feb 2026
Cited by 5 | Viewed by 1550
Abstract
With the advancement of high-end manufacturing, the application of difficult-to-machine materials such as titanium alloys and superalloys is becoming increasingly widespread. Their inherent material properties pose challenges during machining, including high cutting temperatures, rapid tool wear, and difficulty in controlling surface quality. Nanofluid [...] Read more.
With the advancement of high-end manufacturing, the application of difficult-to-machine materials such as titanium alloys and superalloys is becoming increasingly widespread. Their inherent material properties pose challenges during machining, including high cutting temperatures, rapid tool wear, and difficulty in controlling surface quality. Nanofluid minimum quantity lubrication (NFMQL) technology, as an advanced lubrication and cooling method, enhances the thermal conductivity and lubricating properties of fluids by uniformly dispersing nanoparticles in the base oil. This paper reviews the preparation methods, advanced atomization techniques, and core mechanisms of NFMQL technology. It focuses on analyzing the effectiveness of this technology in four major machining processes, turning, milling, grinding, and drilling, for typical materials such as titanium alloys, steel, and superalloys. Compared to dry cutting, conventional MQL, and poured cooling, NFMQL reduces cutting forces/torque, cutting temperatures, tool wear, and surface roughness while improving material removal rates, machining accuracy, and surface integrity. This paper concludes by summarizing the technology’s advantages, current challenges, and future research directions. Full article
(This article belongs to the Special Issue Minimum Quantity Lubrication (MQL): Advances, Applications, and Future Perspectives)
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41 pages, 16361 KB  
Review
Progress on Sustainable Cryogenic Machining of Hard-to-Cut Material and Greener Processing Techniques: A Combined Machinability and Sustainability Perspective
by Shafahat Ali, Said Abdallah, Salman Pervaiz and Ibrahim Deiab
Lubricants 2025, 13(8), 322; https://doi.org/10.3390/lubricants13080322 - 23 Jul 2025
Cited by 7 | Viewed by 5097
Abstract
The current research trends of production engineering are based on optimizing the machining process concerning human and environmental factors. High-performance materials, such as hardened steels, nickel-based alloys, fiber-reinforced polymer (FRP) composites, and titanium alloys, are classified as hard-to-cut due to their ability to [...] Read more.
The current research trends of production engineering are based on optimizing the machining process concerning human and environmental factors. High-performance materials, such as hardened steels, nickel-based alloys, fiber-reinforced polymer (FRP) composites, and titanium alloys, are classified as hard-to-cut due to their ability to maintain strength at high operating temperatures. Due to these characteristics, such materials are employed in applications such as aerospace, marine, energy generation, and structural. The purpose of this article is to investigate the machinability of these alloys under various cutting conditions. The purpose of this article is to compare cryogenic cooling and cryogenic processing from the perspective of machinability and sustainability in the manufacturing process. Compared to conventional machining, hybrid techniques, which mix cryogenic and minimal quantity lubricant, led to significantly reduced cutting forces of 40–50%, cutting temperatures and surface finishes by approximately 20–30% and more than 40%, respectively. A carbon footprint is determined by several factors including power consumption, energy requirements, and carbon dioxide emissions. As a result of the cryogenic technology, the energy consumption, power consumption, and CO2 emissions were reduced by 40%, 28%, and 35%. Full article
(This article belongs to the Special Issue Minimum Quantity Lubrication (MQL): Advances, Applications, and Future Perspectives)
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