Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Tayeh, Tareq"'
Within smart manufacturing, data driven techniques are commonly adopted for condition monitoring and fault diagnosis of rotating machinery. Classical approaches use supervised learning where a classifier is trained on labeled data to predict or class
Externí odkaz:
http://arxiv.org/abs/2212.14550
As a substantial amount of multivariate time series data is being produced by the complex systems in Smart Manufacturing, improved anomaly detection frameworks are needed to reduce the operational risks and the monitoring burden placed on the system
Externí odkaz:
http://arxiv.org/abs/2201.09172
Autor:
Tayeh, Tareq, Shami, Abdallah
As systems in smart manufacturing become increasingly complex, producing an abundance of data, the potential for production failures becomes increasingly more likely. There arises the need to minimize or eradicate production failures, one of which is
Externí odkaz:
http://arxiv.org/abs/2107.05053
Convolutional Neural Network (CNN) techniques have proven to be very useful in image-based anomaly detection applications. CNN can be used as deep features extractor where other anomaly detection techniques are applied on these features. For this sce
Externí odkaz:
http://arxiv.org/abs/2011.06210
Surface anomaly detection plays an important quality control role in many manufacturing industries to reduce scrap production. Machine-based visual inspections have been utilized in recent years to conduct this task instead of human experts. In parti
Externí odkaz:
http://arxiv.org/abs/2011.04121
Autor:
Tayeh, Tareq
Publikováno v:
Electronic Thesis and Dissertation Repository
The smart manufacturing evolution enables financial and operational improvements across the manufacturing industry. However, smart manufacturing encompasses complex, interconnected systems which can fail at any time. To address this challenge, a nove
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1548::087ae6b87cd4d593e0e42a3f5abea8a2
https://ir.lib.uwo.ca/context/etd/article/10596/viewcontent/Tareq_Thesis_2021.pdf
https://ir.lib.uwo.ca/context/etd/article/10596/viewcontent/Tareq_Thesis_2021.pdf