Machine Learning for industrial applications: A comprehensive literature review
Abstract Machine Learning (ML) is a branch of artificial intelligence that studies algorithms
able to learn autonomously, directly from the input data. Over the last decade, ML …
able to learn autonomously, directly from the input data. Over the last decade, ML …
A review of indirect tool condition monitoring systems and decision-making methods in turning: Critical analysis and trends
The complex structure of turning aggravates obtaining the desired results in terms of tool
wear and surface roughness. The existence of high temperature and pressure make difficult …
wear and surface roughness. The existence of high temperature and pressure make difficult …
Machine learning in manufacturing: advantages, challenges, and applications
The nature of manufacturing systems faces ever more complex, dynamic and at times even
chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an …
chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an …
A cost-sensitive deep belief network for imbalanced classification
Imbalanced data with a skewed class distribution are common in many real-world
applications. Deep Belief Network (DBN) is a machine learning technique that is effective in …
applications. Deep Belief Network (DBN) is a machine learning technique that is effective in …
Tool wear classification using time series imaging and deep learning
Tool condition monitoring (TCM) has become essential to achieve high-quality machining as
well as cost-effective production. Identification of the cutting tool state during machining …
well as cost-effective production. Identification of the cutting tool state during machining …
[HTML][HTML] Identification of tool wear using acoustic emission signal and machine learning methods
P Twardowski, M Tabaszewski, M Wiciak–Pikuła… - Precision …, 2021 - Elsevier
The work concerns the monitoring of the edge condition based on acoustic emission (AE)
signals. The tool edge condition was determined by the wear width on the flank face. The …
signals. The tool edge condition was determined by the wear width on the flank face. The …
Support vector machine in machine condition monitoring and fault diagnosis
A Widodo, BS Yang - Mechanical systems and signal processing, 2007 - Elsevier
Recently, the issue of machine condition monitoring and fault diagnosis as a part of
maintenance system became global due to the potential advantages to be gained from …
maintenance system became global due to the potential advantages to be gained from …
In-process tool condition monitoring in compliant abrasive belt grinding process using support vector machine and genetic algorithm
Industrial interest in tool condition monitoring for compliant coated abrasives has
significantly augmented in recent years as unlike other abrasive machining processes the …
significantly augmented in recent years as unlike other abrasive machining processes the …
In situ monitoring of FDM machine condition via acoustic emission
H Wu, Y Wang, Z Yu - The International Journal of Advanced …, 2016 - Springer
Fused deposition modeling (FDM) is one of the most popular additive manufacturing
technologies for fabricating prototypes with complex geometry and different materials …
technologies for fabricating prototypes with complex geometry and different materials …
On-line tool wear monitoring under variable milling conditions based on a condition-adaptive hidden semi-Markov model (CAHSMM)
S Yan, L Sui, S Wang, Y Sun - Mechanical Systems and Signal Processing, 2023 - Elsevier
Since tool wear during machining process imposes a significant limitation on production
quality as well as efficiency, on-line tool wear monitoring (TWM) is one of considerably …
quality as well as efficiency, on-line tool wear monitoring (TWM) is one of considerably …