Investigation of Water-Based Hybrid Nanofluid on Tribological Performance in Minimum Quantity Lubrication Grinding of Difficult-to-Grind Materials DOI

Pirsab Attar,

Rajeshkumar Madarkar,

Sudarsan Ghosh

et al.

Published: Jan. 1, 2024

This study explores the grindability and sustainability, focusing on tribological lubrication capabilities of water-soluble hybrid nanofluid under minimum quantity (MQL) conditions during grinding Nimonic-90. Nanofluids were prepared by adding 0.25%, 0.75%, 1.25% volumetric concentrations Al2O3, GnP nanoparticles into deionized (DI) water. The thermal conductivity, contact angle, dynamic viscosity nanofluids characterized. Specific tangential forces, specific normal coefficient friction, surface roughness reduced approximately 37%, 25%, 17%, 11%, respectively, compared to pure Al2O3 based 29%, 14%, 12%, relative nanofluid. Consequently, a 0.75% concentration water-based emerged as most promising cutting fluid.

Language: Английский

Bibliometric analysis and research trends in minimum quantity lubrication for reducing cutting forces DOI
Chen Ji, Rui Sheng,

Hao Wu

et al.

The International Journal of Advanced Manufacturing Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 21, 2024

Language: Английский

Citations

4
Biological Bone and Replacement Materials in Grinding: Force Model and Processing Capability DOI

Xu Kong,

Chuankun Li, Zhonghao Li

et al.

Intelligent and sustainable manufacturing, Journal Year: 2025, Volume and Issue: 2(1), P. 10003 - 10003

Published: Jan. 1, 2025

Language: Английский

Citations

0
The 40Cr surface hardening mechanism by pre-stressed dry grinding DOI
Chao Cai-xia, He Zhang, Cong Sun

et al.

The International Journal of Advanced Manufacturing Technology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 20, 2025

Language: Английский

Citations

0
Eco-friendly Grinding: A Bibliometric and Knowledge Map Analysis DOI Creative Commons

Hao Wu,

Jixin Liu, Chen Ji

et al.

Chinese Journal of Mechanical Engineering, Journal Year: 2025, Volume and Issue: 38(1)

Published: March 27, 2025

Abstract As the manufacturing industry shifts toward environmentally sustainable practices, grinding—a high-precision processing method—is commonly used to ensure final workpiece dimensions and surface quality. The greening of grinding processes has emerged as an important challenge for both academia industry. Numerous studies proposing different methods have increased rapidly; however, technical mechanisms development trends remain unclear. This paper applies bibliometric analyze relevant articles published on WOS from 2008 2023. Results show that China highest number publications (45.38%), with research institutions primarily located in China, India, Brazil. Among publishing journals, 70% are classified Q2 or above. Additionally, popular authors influential this field identified. Keyword frequency hotspot literature analysis reveal focuses minimal quantity lubrication (MQL) grinding, especially using biolubricants nanoparticles improve performance. article reviews effects MQL. It further examines how multi-energy applications enhance MQL by influencing droplet atomization, wettability, machining A low-temperature improves heat exchange capacity droplets, while electrostatic enhances contact angles dispersion. Ultrasonic energy atomization biolubricants, magnetic fields facilitate nanoparticle penetration into zone, reducing forces. innovations wheel structures solid can reduce temperatures presents a comprehensive review eco-friendly hotspots, providing support theoretical guidance

Language: Английский

Citations

0
Active learning regression quality prediction model and grinding mechanism for ceramic bearing grinding processing DOI Creative Commons

Longfei Gao,

Yuhou Wu, Jian Sun

et al.

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(4), P. e0320494 - e0320494

Published: April 7, 2025

The study aims to explore quality prediction in ceramic bearing grinding processing, with particular focus on the effect of parameters surface roughness. uses active learning regression model for construction and optimization, empirical analysis under different conditions. At same time, various deep models are utilized conduct experiments processing. experimental setup covers a variety parameters, including wheel linear speed, depth feed rate, ensure accuracy reliability According results, when increases 21 μm, average training loss further decreases 0.03622, roughness Ra value significantly 0.1624 μm. In addition, experiment also found that increasing velocity moderately adjusting can improve machining quality. For example, is 45 m/s 0.015 mm, drops 0.1876 results not only provide theoretical support processing bearings, but basis optimization actual production, which has an important industrial application value.

Language: Английский

Citations

0
Sustainable orthogonal turn-mill process parameter decision-making based on specific consumption energy model and NSGA-II multi-objective optimization algorithm DOI Creative Commons

Ke-Er Tang,

Guo Lin, Chun‐Wei Liu

et al.

The International Journal of Advanced Manufacturing Technology, Journal Year: 2025, Volume and Issue: unknown

Published: April 12, 2025

Language: Английский

Citations

0
Investigation of Water-Based Hybrid Nanofluid on Tribological Performance in Minimum Quantity Lubrication Grinding of Nimonic-90 Superalloy DOI

Pirsab Attar,

Rajeshkumar Madarkar,

Sudarsan Ghosh

et al.

Journal of Materials Engineering and Performance, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 17, 2024

Language: Английский

Citations

2
Effects of ultrasonic nanolubrication on milling performance and surface integrity of SiCp/Al composites DOI

Shuguo Hu,

Xiaoming Wang, Teng Gao

et al.

The International Journal of Advanced Manufacturing Technology, Journal Year: 2024, Volume and Issue: 135(9-10), P. 4865 - 4878

Published: Nov. 13, 2024

Language: Английский

Citations

2
Development of a Wearable Electromyographic Sensor with Aerosol Jet Printing Technology DOI Creative Commons

Stefano Perilli,

Massimo Di Pietro,

Emanuele Mantini

et al.

Bioengineering, Journal Year: 2024, Volume and Issue: 11(12), P. 1283 - 1283

Published: Dec. 17, 2024

Electromyographic (EMG) sensors are essential tools for analyzing muscle activity, but traditional designs often face challenges such as motion artifacts, signal variability, and limited wearability. This study introduces a novel EMG sensor fabricated using Aerosol Jet Printing (AJP) technology that addresses these limitations with focus on precision, flexibility, stability. The innovative design minimizes air interposition at the skin–electrode interface, thereby reducing variability improving quality. AJP enables precise deposition of conductive materials onto flexible substrates, achieving thinner more conformable enhances user comfort Performance testing compared to commercially available alternatives, highlighting its superior impedance stability across frequencies, even under mechanical stress. Physiological validation human participant confirmed sensor’s ability accurately capture activity during rest voluntary contractions, clear differentiation between low high states. findings highlight potential diverse applications, clinical diagnostics, rehabilitation, sports performance monitoring. work establishes approach designing wearable sensors, providing pathway further advancements in miniaturization, strain-insensitive designs, real-world deployment. Future research will explore optimization broader applications larger populations.

Language: Английский

Citations

1
Investigation of Water-Based Hybrid Nanofluid on Tribological Performance in Minimum Quantity Lubrication Grinding of Difficult-to-Grind Materials DOI

Pirsab Attar,

Rajeshkumar Madarkar,

Sudarsan Ghosh

et al.

Published: Jan. 1, 2024

This study explores the grindability and sustainability, focusing on tribological lubrication capabilities of water-soluble hybrid nanofluid under minimum quantity (MQL) conditions during grinding Nimonic-90. Nanofluids were prepared by adding 0.25%, 0.75%, 1.25% volumetric concentrations Al2O3, GnP nanoparticles into deionized (DI) water. The thermal conductivity, contact angle, dynamic viscosity nanofluids characterized. Specific tangential forces, specific normal coefficient friction, surface roughness reduced approximately 37%, 25%, 17%, 11%, respectively, compared to pure Al2O3 based 29%, 14%, 12%, relative nanofluid. Consequently, a 0.75% concentration water-based emerged as most promising cutting fluid.

Language: Английский

Citations

0