Review of tool condition monitoring in machining and opportunities for deep learning
Tool condition monitoring and machine tool diagnostics are performed using advanced
sensors and computational intelligence to predict and avoid adverse conditions for cutting …
sensors and computational intelligence to predict and avoid adverse conditions for cutting …
Application of sophisticated sensors to advance the monitoring of machining processes: analysis and holistic review
Response measurement of various functionality states of machines is an inevitable part of
smooth production. An effectively efficient measurement and control system of the machinery …
smooth production. An effectively efficient measurement and control system of the machinery …
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 process endurance. Industries …
influences the surface roughness, power consumption, and process endurance. Industries …
Novel fractional-order convolutional neural network based chatter diagnosis approach in turning process with chaos error mapping
The chatter not only brings about poor surface quality of the workpiece but also causes the
tool wear and then leads to the increase in production cost over time. For this reason, it …
tool wear and then leads to the increase in production cost over time. For this reason, it …
Prediction and analysis of material removal characteristics for robotic belt grinding based on single spherical abrasive grain model
Comprehensive study of the microscopic material removal mechanism remains an open
challenge facing the robotic belt grinding of complex geometries. In the present paper, a …
challenge facing the robotic belt grinding of complex geometries. In the present paper, a …
In-process virtual verification of weld seam removal in robotic abrasive belt grinding process using deep learning
Transforming the manufacturing environment from manually operated production units to
unsupervised robotic machining centres requires a presence of reliable in-process …
unsupervised robotic machining centres requires a presence of reliable in-process …
Tool wear monitoring for complex part milling based on deep learning
X Zhang, C Han, M Luo, D Zhang - Applied sciences, 2020 - mdpi.com
Tool wear monitoring is necessary for cost reduction and productivity improvement in the
machining industry. Machine learning has been proven to be an effective means of tool wear …
machining industry. Machine learning has been proven to be an effective means of tool wear …
Tool life prognostics in CNC turning of AISI 4140 steel using neural network based on computer vision
One of the essential requirements for intelligent manufacturing is the low cost and reliable
predictions of the tool life during machining. It is crucial to monitor the condition of the cutting …
predictions of the tool life during machining. It is crucial to monitor the condition of the cutting …
Neural network based instant parameter prediction for wireless sensor network optimization models
Optimal operation configuration of a Wireless Sensor Network (WSN) can be determined by
utilizing exact mathematical programming techniques such as Mixed Integer Programming …
utilizing exact mathematical programming techniques such as Mixed Integer Programming …
Intelligent chatter detection in milling using vibration data features and deep multi-layer perceptron
B Sener, G Serin, MU Gudelek… - … Conference on Big …, 2020 - ieeexplore.ieee.org
Milling is a highly crucial machining process in the modern industry. With the recent trends of
Industry 4.0, it is becoming more common to implement Artificial Intelligence (AI) methods to …
Industry 4.0, it is becoming more common to implement Artificial Intelligence (AI) methods to …