Improving milling force predictions: A hybrid approach integrating physics-based simulation and machine learning for remarkable accuracy across diverse unseen …
The prediction of milling forces has been addressed using a range of methods, including
physics-based models and data-driven approaches. Analytical predictions that rely on …
physics-based models and data-driven approaches. Analytical predictions that rely on …
Physics-informed tool wear prediction in turning process: A thermo-mechanical wear-included force model integrated with machine learning
Tool wear prediction is essential for increasing production efficiency, improving product
quality and reducing manufacturing costs. However, most of the existing studies are either …
quality and reducing manufacturing costs. However, most of the existing studies are either …
Cutting model integrated digital twin–based process monitoring in small-batch machining
L Bai, J Zhang, J Yan, LN López de Lacalle… - … International Journal of …, 2025 - Springer
The success of machining process automation hinges primarily on the effectiveness of the
monitoring and adaptive control systems. A new digital twin–based process monitoring …
monitoring and adaptive control systems. A new digital twin–based process monitoring …
[HTML][HTML] A Short Review: Tribology in Machining to Understand Conventional and Latest Modeling Methods with Machine Learning
S Kano - Machines, 2025 - mdpi.com
Tribology plays a critical role in machining technologies. Friction is an essential factor in
processes such as composite material machining and bonding. This short review highlights …
processes such as composite material machining and bonding. This short review highlights …
Milling process monitoring based on intelligent real-time parameter identification for unmanned manufacturing
This study addresses the critical need for intelligent process monitoring in unmanned
manufacturing through real-time fault detection. The proposed hybrid approach, which is …
manufacturing through real-time fault detection. The proposed hybrid approach, which is …
Fault diagnosis of a CNC hobbing cutter through machine learning using three axis vibration data
This research presents a novel approach to fault diagnosis for CNC hobbing cutters using
machine learning techniques, leveraging three-axis vibration data to ensure machining …
machine learning techniques, leveraging three-axis vibration data to ensure machining …
Advancing PUF Security Machine Learning Assisted Modeling Attacks
Physically Unclonable Functions (PUFs) works as an essential component for hardware
security, using their inherent unpredictability to prevent unauthorized access. However …
security, using their inherent unpredictability to prevent unauthorized access. However …
Unveiling mental health with machine learning and deep learning: Exploring applications and navigating challenges
In today fast-paced society, psychological health issues such as anxiety, depression, and
stress have become increasingly prevalent across diverse populations. This paper explores …
stress have become increasingly prevalent across diverse populations. This paper explores …