Review of transfer learning in modeling additive manufacturing processes
Modeling plays an important role in the additive manufacturing (AM) process and quality
control. In practice, however, only limited data are available for each product due to the …
control. In practice, however, only limited data are available for each product due to the …
Advanced data collection and analysis in data-driven manufacturing process
The rapidly increasing demand and complexity of manufacturing process potentiates the
usage of manufacturing data with the highest priority to achieve precise analyze and control …
usage of manufacturing data with the highest priority to achieve precise analyze and control …
Active vibration suppression in robotic milling using optimal control
Abstract Six degree-of-freedom (6-dof) industrial robots are attractive alternatives to
Computer Numerical Control (CNC) machine tools for milling of large parts because of their …
Computer Numerical Control (CNC) machine tools for milling of large parts because of their …
A hybrid transfer learning scheme for remaining useful life prediction and cycle life test optimization of different formulation Li-ion power batteries
Long-term cycle life test in battery development is crucial for formulations selection but time-
consuming and high-cost. To shorten cycle test with estimated lifespan, a prediction-based …
consuming and high-cost. To shorten cycle test with estimated lifespan, a prediction-based …
Pose optimization in robotic machining using static and dynamic stiffness models
Industrial robots are typically not used for milling of hard materials due to their low stiffness
compared to traditional machine tools. Due to milling being a five degree of freedom (dof) …
compared to traditional machine tools. Due to milling being a five degree of freedom (dof) …
A state-of-the-art review on chatter stability in machining thin− walled parts
Y Sun, M Zheng, S Jiang, D Zhan, R Wang - Machines, 2023 - mdpi.com
Thin− walled parts are widely used in many important fields because of performance and
structural lightweight requirements. They are critical parts because they usually carry the …
structural lightweight requirements. They are critical parts because they usually carry the …
Recent advances on machine learning applications in machining processes
F Aggogeri, N Pellegrini, FL Tagliani - Applied sciences, 2021 - mdpi.com
This study aims to present an overall review of the recent research status regarding Machine
Learning (ML) applications in machining processes. In the current industrial systems …
Learning (ML) applications in machining processes. In the current industrial systems …
A weighted adaptive transfer learning for tool tip dynamics prediction of different machine tools
In the batch machining of manufacturing enterprises, there are always different machine
tools of the same type used. Due to the influence of the uncertain degree of deterioration …
tools of the same type used. Due to the influence of the uncertain degree of deterioration …
Hybrid statistical modelling of the frequency response function of industrial robots
Abstract Models that predict the Frequency Response Function (FRF) of six degree-of-
freedom (6-dof) industrial robots used for machining operations such as milling are usually …
freedom (6-dof) industrial robots used for machining operations such as milling are usually …
Predictive modeling for machining power based on multi-source transfer learning in metal cutting
Energy efficiency has become crucial in the metal cutting industry. Machining power has
therefore become an important metric because it directly affects the energy consumed …
therefore become an important metric because it directly affects the energy consumed …