Fault detection and diagnosis is one of the most critical components of preventing accidents
and ensuring the system safety of industrial processes. In this paper, we propose an …

Rare event prediction involves identifying and forecasting events with a low probability using
machine learning and data analysis. Due to the imbalanced data distributions, where the …

Anomaly detection is critical in the Internet of Things (IoT) systems due to its wide
applications for building smart cities, such as quality control in manufacturing, intrusion …

Excessive and untimely maintenance prompts economic losses and unnecessary workload.
Therefore, predictive maintenance models are developed to estimate the right time for …

Deep learning is an art. But it has some boundaries. Learning the boundaries is essential to
develop working solutions and, ultimately, push them for novel creations. For example …

Quick process shift detection and lower out-of-control run length are essential for monitoring
the production process, especially in modern smart manufacturing. Specifically, the out-of …

Rare event detection (RED) involves the identification and detection of events characterized
by low frequency of occurrences, but of high importance or impact. This paper presents a …

Deep learning has been applied successfully in sequence understanding and translation
problems, especially in univariate, unimodal contexts, where large number of supervision …

Bearings are vital part of rotary machines. A failure of bearing has a negative impact on
schedules, production operation and even human casualties. Therefore, in prior achieving …

Manufacturers are struggling to use data from multiple products production lines to predict
rare events. Improving the quality of training data is a common way to improve the …