Quo vadis artificial intelligence?

Y Jiang, X Li, H Luo, S Yin, O Kaynak - Discover Artificial Intelligence, 2022 - Springer
The study of artificial intelligence (AI) has been a continuous endeavor of scientists and
engineers for over 65 years. The simple contention is that human-created machines can do …

Machine learning and data mining in manufacturing

A Dogan, D Birant - Expert Systems with Applications, 2021 - Elsevier
Manufacturing organizations need to use different kinds of techniques and tools in order to
fulfill their foundation goals. In this aspect, using machine learning (ML) and data mining …

A review on deep learning techniques for IoT data

K Lakshmanna, R Kaluri, N Gundluru, ZS Alzamil… - Electronics, 2022 - mdpi.com
Continuous growth in software, hardware and internet technology has enabled the growth of
internet-based sensor tools that provide physical world observations and data …

Fault detection and diagnosis for rotating machinery: A model based on convolutional LSTM, Fast Fourier and continuous wavelet transforms

M Jalayer, C Orsenigo, C Vercellis - Computers in Industry, 2021 - Elsevier
Abstract Fault Detection and Diagnosis (FDD) of rotating machinery plays a key role in
reducing the maintenance costs of the manufacturing systems. How to improve the FDD …

[HTML][HTML] A review on autoencoder based representation learning for fault detection and diagnosis in industrial processes

J Qian, Z Song, Y Yao, Z Zhu, X Zhang - Chemometrics and Intelligent …, 2022 - Elsevier
Process monitoring technologies play a key role in maintaining the steady state of industrial
processes. However, with the increasing complexity of modern industrial processes …

Deep learning for IoT big data and streaming analytics: A survey

M Mohammadi, A Al-Fuqaha, S Sorour… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
In the era of the Internet of Things (IoT), an enormous amount of sensing devices collect
and/or generate various sensory data over time for a wide range of fields and applications …

A deep learning approach to network intrusion detection

N Shone, TN Ngoc, VD Phai… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Network intrusion detection systems (NIDSs) play a crucial role in defending computer
networks. However, there are concerns regarding the feasibility and sustainability of current …

A review on fault detection and process diagnostics in industrial processes

YJ Park, SKS Fan, CY Hsu - Processes, 2020 - mdpi.com
The main roles of fault detection and diagnosis (FDD) for industrial processes are to make
an effective indicator which can identify faulty status of a process and then to take a proper …

Convolutional neural network for wafer surface defect classification and the detection of unknown defect class

S Cheon, H Lee, CO Kim, SH Lee - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
An automatic defect classification (ADC) system identifies and classifies wafer surface
defects using scanning electron microscope images. By classifying defects, manufacturers …

Recent advances in sensor fault diagnosis: A review

D Li, Y Wang, J Wang, C Wang, Y Duan - Sensors and Actuators A …, 2020 - Elsevier
As an essential component of data acquisition systems, sensors have been widely used,
especially in industrial and agricultural sectors. However, sensors are also prone to faults …