Lstm-autoencoder for vibration anomaly detection in vertical carousel storage and retrieval system (vcsrs)

JS Do, AB Kareem, JW Hur - Sensors, 2023 - mdpi.com
Industry 5.0, also known as the “smart factory”, is an evolution of manufacturing technology
that utilizes advanced data analytics and machine learning techniques to optimize …

A modular ice cream factory dataset on anomalies in sensors to support machine learning research in manufacturing systems

T Markovic, M Leon, B Leander, S Punnekkat - IEEE Access, 2023 - ieeexplore.ieee.org
A small deviation in manufacturing systems can cause huge economic losses, and all
components and sensors in the system must be continuously monitored to provide an …

Supervised-learning-based intelligent fault diagnosis for mechanical equipment

G Hong, D Suh - IEEE Access, 2021 - ieeexplore.ieee.org
Recently, anomaly detection for improving the productivity of machinery in industrial
environments has drawn considerable attention. As large-scale data collection and …

Autocorrelation integrated gaussian based anomaly detection using sensory data in industrial manufacturing

A Saci, A Al-Dweik, A Shami - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
In industrial processes, early detection of anomalies is crucial for reducing process failures,
meeting the quality assurance (QA) requirements, and lowering raw material wastage …

Fast adaptive RNN encoder–decoder for anomaly detection in SMD assembly machine

YH Park, ID Yun - Sensors, 2018 - mdpi.com
Surface Mounted Device (SMD) assembly machine manufactures various products on a
flexible manufacturing line. An anomaly detection model that can adapt to the various …

Industrial internet of things and unsupervised deep learning enabled real-time occupational safety monitoring in cold storage warehouse

X Zhan, W Wu, L Shen, W Liao, Z Zhao, J Xia - Safety science, 2022 - Elsevier
Occupational safety and health (OSH) has always been a big concern in the labor-intensive
warehouse industry, especially under peculiar circumstances like a low temperature …

Smart anomaly detection and prediction for assembly process maintenance in compliance with industry 4.0

P Tanuska, L Spendla, M Kebisek, R Duris, M Stremy - Sensors, 2021 - mdpi.com
One of the big problems of today's manufacturing companies is the risks of the assembly line
unexpected cessation. Although planned and well-performed maintenance will significantly …

Vibration-based anomaly detection using LSTM/SVM approaches

K Vos, Z Peng, C Jenkins, MR Shahriar… - … Systems and Signal …, 2022 - Elsevier
Fault detection is a critical step for machine condition monitoring and maintenance. With
advances in machine learning technologies, automated faulty condition identification can be …

[PDF][PDF] Anomaly detection and diagnosis in manufacturing systems: A comparative study of statistical, machine learning and deep learning techniques

K Zope, K Singh, S Nistala, A Basak, P Rathore… - Annu. Conf. PHM …, 2019 - academia.edu
Multivariate sensor data collected from manufacturing and process industries represents
actual operational behavior and can be used for predictive maintenance of the plants …

A deep learning approach for anomaly detection based on SAE and LSTM in mechanical equipment

Z Li, J Li, Y Wang, K Wang - The International Journal of Advanced …, 2019 - Springer
Anomaly in mechanical systems may cause equipment to break down with serious safety,
environment, and economic impact. Since many mechanical equipment usually operates …