Sounds and acoustic emission-based early fault diagnosis of induction motor: A review study
O AlShorman, F Alkahatni, M Masadeh… - Advances in …, 2021 - journals.sagepub.com
Nowadays, condition-based maintenance (CBM) and fault diagnosis (FD) of rotating
machinery (RM) has a vital role in the modern industrial world. However, the remaining …
machinery (RM) has a vital role in the modern industrial world. However, the remaining …
Twenty‐year retrospection on green manufacturing: A bibliometric perspective
In the modern age of Industry 4.0 and manufacturing servitisation, energy saving and
environment consciousness are regarded as vital themes in manufacturing processes to …
environment consciousness are regarded as vital themes in manufacturing processes to …
Detecting anomalies in time series data from a manufacturing system using recurrent neural networks
Y Wang, M Perry, D Whitlock, JW Sutherland - Journal of Manufacturing …, 2022 - Elsevier
The industrial internet of things allows manufacturers to acquire large amounts of data. This
opportunity, assuming the right methods are available, allows manufacturers to find …
opportunity, assuming the right methods are available, allows manufacturers to find …
A novel approach for tool condition monitoring based on transfer learning of deep neural networks using time–frequency images
Y Li, Z Zhao, Y Fu, Q Chen - Journal of Intelligent Manufacturing, 2024 - Springer
Traditional tool condition monitoring methods developed in an ideal environment are not
universal in multiple working conditions considering different signal sources and recognition …
universal in multiple working conditions considering different signal sources and recognition …
Industrial artificial intelligence, smart connected sensors, and big data-driven decision-making processes in Internet of Things-based real-time production logistics
R Davis, M Vochozka, J Vrbka, O Neguriţă - … , Management and Financial …, 2020 - ceeol.com
Employing recent research results covering Internet of Things-based real-time production
logistics, and building our argument by drawing on data collected from Catapult, Deloitte …
logistics, and building our argument by drawing on data collected from Catapult, Deloitte …
Anomaly detection and inter-sensor transfer learning on smart manufacturing datasets
Smart manufacturing systems are considered the next generation of manufacturing
applications. One important goal of the smart manufacturing system is to rapidly detect and …
applications. One important goal of the smart manufacturing system is to rapidly detect and …
A deep-learning-based multi-modal sensor fusion approach for detection of equipment faults
O Kullu, E Cinar - Machines, 2022 - mdpi.com
Condition monitoring is a part of the predictive maintenance approach applied to detect and
prevent unexpected equipment failures by monitoring machine conditions. Early detection of …
prevent unexpected equipment failures by monitoring machine conditions. Early detection of …
Cyber-physical production networks, artificial intelligence-based decision-making algorithms, and big data-driven innovation in Industry 4.0-based manufacturing …
R Davidson - Economics, Management, and Financial Markets, 2020 - ceeol.com
Despite the relevance of Industry 4.0-based manufacturing systems, only limited research
has been conducted on this topic. Using and replicating data from Accenture, Deloitte, MHI …
has been conducted on this topic. Using and replicating data from Accenture, Deloitte, MHI …
Anomaly detection through transfer learning in agriculture and manufacturing IoT systems
IoT systems have been facing increasingly sophisticated technical problems due to the
growing complexity of these systems and their fast deployment practices. Consequently, IoT …
growing complexity of these systems and their fast deployment practices. Consequently, IoT …
A flame imaging-based online deep learning model for predicting NOₓ emissions from an oxy-biomass combustion process
To reduce NO x (nitrogen oxide) emissions from fossil fuel and biomass-fired power plants,
online prediction of NO x emissions is important in the plant operation. Data-driven models …
online prediction of NO x emissions is important in the plant operation. Data-driven models …