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Tool wear classification in precision machining using distance metrics and unsupervised machine learning
This article reports an unsupervised approach for estimation of the tool condition in precision machining processes. Three campaigns of...
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Machine vision-based recognition of elastic abrasive tool wear and its influence on machining performance
This study presents a novel Hunter-Prey Optimization (HPO)-optimized Otsu algorithm in tool wear assessment and machining process quality control....
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An imbalanced data learning approach for tool wear monitoring based on data augmentation
During cutting operations, tool condition monitoring (TCM) is essential for maintaining safety and cost optimization, especially in the accelerated...
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Tool wear prediction in milling CFRP with different fiber orientations based on multi-channel 1DCNN-LSTM
In the machining of carbon fiber reinforced polymer (CFRP) components, tool wear grows rapidly due to the highly abrasive property of carbon fibers,...
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Evaluation of data augmentation and loss functions in semantic image segmentation for drilling tool wear detection
Tool wear monitoring is crucial for quality control and cost reduction in manufacturing processes, of which drilling applications are one example....
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A Generative AI approach to improve in-situ vision tool wear monitoring with scarce data
Most aerospace turbine casings are mechanised using a vertical lathe. This paper presents a tool wear monitoring system using computer vision that...
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Cross-domain adaptation network based on attention mechanism for tool wear prediction
On-machine monitoring of tool wear is of great significance in machining processes to enhance machining efficiencies and reduce cost. For the...
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Tool wear condition monitoring across machining processes based on feature transfer by deep adversarial domain confusion network
Deep learning-based data-driven methods have been successfully developed in tool wear condition monitoring (TWCM), relying on the massive available...
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An edge-based algorithm for tool wear monitoring in repetitive milling processes
In the era of Industry 4.0, cloud computing has attracted a lot of attention from industrial organizations in realizing smart manufacturing. However,...
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An approach for tool wear prediction using customized DenseNet and GRU integrated model based on multi-sensor feature fusion
An accurate prediction of the machining tool condition during the cutting process is crucial for enhancing the tool life, improving the production...
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A novel approach of tool condition monitoring in sustainable machining of Ni alloy with transfer learning models
Cutting tool condition is crucial in metal cutting. In-process tool failures significantly influences the surface roughness, power consumption, and...
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Appending-inspired multivariate time series association fusion for tool condition monitoring
In intelligent machining, tool condition monitoring (TCM) is crucial to improving tool efficiency and machining accuracy, which requires the...
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Data-driven indirect punch wear monitoring in sheet-metal stam** processes
The wear state of the punch in sheet-metal stam** processes cannot be directly observed, necessitating the use of indirect methods to infer its...
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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...
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Development of a cyber physical production system framework for smart tool health management
More and more organisations are trying to install tool health analytics dashboards for CNC machines to avoid unexpected failures, maintain machining...
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Relating wear stages in sheet metal forming based on short- and long-term force signal variations
Monitoring systems in sheet metal forming cannot rely on direct measurements of the physical condition of interest because the space between the die...
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Identification of cutting tool wear condition in turning using self-organizing map trained with imbalanced data
One of the most important parameters in machining process is tool wear. Thus, monitoring the wear of cutting tools is essential to ensure product...
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Predicting tool wear size across multi-cutting conditions using advanced machine learning techniques
The need to monitor tool wear is crucial, particularly in advanced manufacturing industries, as it aims to maximise the lifespan of the cutting tool...
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Machining tool identification utilizing temporal 3D point clouds
The manufacturing domain is regarded as one of the most important engineering areas. Recently, smart manufacturing merges the use of sensors,...
