Artificial intelligence systems for tool condition monitoring in machining: Analysis and critical review
The wear of cutting tools, cutting force determination, surface roughness variations and other
machining responses are of keen interest to latest researchers. The variations of these …
machining responses are of keen interest to latest researchers. The variations of these …
Physics guided neural network for machining tool wear prediction
Tool wear prediction is of significance to improve the safety and reliability of machining tools,
given their widespread applications in nearly every branch of manufacturing. Mathematical …
given their widespread applications in nearly every branch of manufacturing. Mathematical …
Monitoring the tool wear, surface roughness and chip formation occurrences using multiple sensors in turning
Tool wear, chip formation and surface roughness of workpiece under different cutting
conditions have been investigated in machining using acoustic emission (AE) and vibration …
conditions have been investigated in machining using acoustic emission (AE) and vibration …
Physics-guided logistic classification for tool life modeling and process parameter optimization in machining
This paper describes a physics-guided logistic classification method for tool life modeling
and process parameter optimization in machining. Tool life is modeled using a classification …
and process parameter optimization in machining. Tool life is modeled using a classification …
Machine learning classification for tool life modeling using production shop-floor tool wear data
Tool wear is an important limitation to machining productivity. Tool wear in machining is
difficult to predict due to large number of influencing variables and tool-to-tool performance …
difficult to predict due to large number of influencing variables and tool-to-tool performance …
Intelligent automation of design and manufacturing in machine tools using an open architecture motion controller
Several issues including accurate programming, proper tool selection, machining feeds and
speeds selection, thermal error compensation, vibration monitoring, etc. contribute …
speeds selection, thermal error compensation, vibration monitoring, etc. contribute …
[HTML][HTML] A realistic full-scale 3D modeling of turning using coupled smoothed particle hydrodynamics and finite element method for predicting cutting forces
Computational modelling is an effective technique for understanding the complex physics of
machining. Large deformations, material separation, and high computational requirements …
machining. Large deformations, material separation, and high computational requirements …
Tool life prediction via SMB-enabled monitor based on BPNN coupling algorithms for sustainable manufacturing
WY Chang, BY Hsu - Ai Edam, 2023 - cambridge.org
The predictive methods of tool wear are usually based on different algorithm predictors,
different source data, and different sensing devices for remaining useful life (RUL). In …
different source data, and different sensing devices for remaining useful life (RUL). In …
[HTML][HTML] Using ensembles for accurate modelling of manufacturing processes in an IoT data-acquisition solution
The development of complex real-time platforms for the Internet of Things (IoT) opens up a
promising future for the diagnosis and the optimization of machining processes. Many issues …
promising future for the diagnosis and the optimization of machining processes. Many issues …
Probabilistic force prediction in cold sheet rolling by Bayesian inference
A primary factor in manufacturing high-quality cold-rolled sheet is the ability to accurately
predict the required rolling force. Rolling force directly influences roll-stack deflections …
predict the required rolling force. Rolling force directly influences roll-stack deflections …