The growing complexity of data derived from Industrial Internet of Things (IIoT) systems
presents substantial challenges for traditional machine-learning techniques, which struggle …

The application of Artificial Intelligence (AI) approaches in industrial maintenance for fault
detection and prediction has gained much attention from scholars and practitioners. This …

Stroke, categorized under cardiovascular and circulatory diseases, is considered the second
foremost cause of death worldwide, causing approximately 11% of deaths annually. Stroke …

Fusarium head blight (FHB) is considered one of the most serious fungal diseases of wheat.
Fusarium resulted in yield losses and contamination of harvested grains with mycotoxins …

Abstract Predictive Maintenance (PdM) is a critical area that is benefiting from the Industry
4.0 advent. Recently, several attempts have been made to apply Machine Learning (ML) to …

Predictive maintenance plays a crucial role across diverse domains, ensuring operational
efficiency and reliability. However, the increasing need for securing predictive maintenance …

A machine learning (ML) approach is introduced to predict the high-cycle fatigue (HCF) life
of selective laser melted (SLM) TA15 titanium alloy, addressing life prediction variability …

Anomaly detection attempts to identify abnormal events that deviate from normality. Since
such events are often rare, data related to this domain is usually imbalanced. In this paper …

Abstract Developments in Machine Learning (ML) in the last years resulted in taking as
granted their usage and their necessity clear in areas such as manufacturing and quality …

This survey presents a comprehensive review of data-driven approaches for industrial asset
maintenance, emphasizing the use of data mining and machine learning techniques …