Since the introduction of the industry 4.0 paradigm, manufacturing companies are investing in the development of algorithmic diagnostic solutions for their industrial equipment, relying …
Z Li, Y Wang, KS Wang - Advances in Manufacturing, 2017 - Springer
Fault diagnosis and prognosis in mechanical systems have been researched and developed in the last few decades at a very rapid rate. However, owing to the high …
Artificial intelligence applications are increasing due to advances in data collection systems, algorithms, and affordability of computing power. Within the manufacturing industry, machine …
W Yan, J Wang, S Lu, M Zhou, X Peng - Processes, 2023 - mdpi.com
In the era of Industry 4.0, highly complex production equipment is becoming increasingly integrated and intelligent, posing new challenges for data-driven process monitoring and …
W Yu, T Dillon, F Mostafa, W Rahayu… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Artificial intelligence, big data, machine learning, cloud computing, and Internet of Things (IoT) are terms which have driven the fourth industrial revolution. The digital revolution has …
Automated fault detection is an important part of a quality control system. It has the potential to increase the overall quality of monitored products and processes. The fault detection of …
N Yassaie, S Gargoum… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In large-scale industrial processes, fault diagnosis is of paramount importance, as faults jeopardize the stability and performance of processes. However, effective fault diagnosis …
Early fault detection, both in equipment and the products in process, is of paramount importance in industrial processes to ensure the quality of the final product, avoid abnormal …
The recent advancements in the fields of artificial intelligence (AI) and machine learning (ML) have affected several research fields, leading to improvements that could not have …