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Arup Dey, Nita Yodo, Om P. Yadav, Ragavanantham Shanmugam and Monsuru Ramoni
Data-driven algorithms have been widely applied in predicting tool wear because of the high prediction performance of the algorithms, availability of data sets, and advancements in computing capabilities in recent years. Although most algorithms are supp...
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Zhimeng Li, Wen Zhong, Weiwen Liao, Yiqun Cai, Jian Zhao and Guofeng Wang
Real-time tool condition monitoring (TCM) is becoming more and more important to meet the increased requirement of reducing downtime and ensuring the machining quality of manufacturing systems. However, it is difficult to satisfy both robustness and effe...
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Jan Duplak, Darina Duplakova and Jozef Zajac
From the point of view of production, it is of fundamental importance to know the cutting parameters at which the new surface of the component was created because only in this way is it possible to understand the nature and properties of the created surf...
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Qingqing Huang, Di Wu, Hao Huang, Yan Zhang and Yan Han
Compared with traditional machine learning algorithms, the convolutional neural network (CNN) has an excellent automatic feature learning ability and can complete the nonlinear representation from original data input to output by itself. However, the CNN...
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Eunyoung Heo and Namhyun Yoo
In numerical control (NC)-based machining, NC data-based tool paths affect both quality and productivity. NC data are generated according to cutting conditions. However, NC data causing excessive cutting load can accelerate tool wear and even result in t...
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Zemin Zhao, Xianli Liu, Caixu Yue, Rongyi Li, Hongyan Zhang and Steven Liang
The prediction and control of milling tool service performance is critical for milling tool design and machining. However, the existing prediction model can hardly quantify tool performance, or precisely describe the relationship between the tool perform...
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Gorka Urbikain, Daniel Olvera, Luis Norberto López de Lacalle, Aitor Beranoagirre and Alex Elías-Zuñiga
The general trend towards lightweight components and stronger but difficult to machine materials leads to a higher probability of vibrations in machining systems. Amongst them, chatter vibrations are an old enemy for machinists with the most dramatic cas...
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Tim Martin, Lith Choummanivong
Pág. 2477 - 2486
Long-term pavement performance (LTPP) monitoring has been conducted in Australia for over 20 years. This research was funded by Austroads (representing federal, state and territory road agencies, local government and the New Zealand road agency) to promo...
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Alexander Bardetsky, Helmi Attia, and Mohamed Elbestawi
Pág. 23 - 30
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Alexander Bardetsky, Helmi Attia, and Mohamed Elbestawi
Pág. 31 - 39
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