Anomaly detection is a crucial aspect for both safety and efficiency of modern process
industries. This paper proposes a two-steps methodology for anomaly detection in industrial …

This article delineates the design and deployment of an innovative real-time water quality
monitoring system tailored for rural regions, focusing on monitoring the water resource …

This paper proposes a novel Transformer-based neural network model for accurate tool
wear estimation to improve production quality and efficiency in intelligent manufacturing …

In this review, we present the recent progress on film metrology focused on the advanced
and novel technologies during the last two decades. This review consists of various …

The Internet of Things (IoT) is characterized by a large number of interconnected devices or
assets. Measurement instruments in the IoT are typically digital in the sense that their …

A novel fault diagnosis method is proposed, depending on a cloud service, for the typical
faults in the hydraulic directional valve. The method, based on the Machine Learning …

The annotation of sensor data with semantic metadata is essential to the goals of automation
and interoperability in the context of Industry 4.0. In this contribution, we outline a semantic …

We consider fault detection in a hydraulic system that maintains multivariate time-series
sensor data. Such a real-world industrial environment could suffer from noisy data resulting …

This paper presents the development of an easy-to-deploy and smart monitoring IoT system
that utilizes vibration measurement devices to assess real-time condition of bulldozers …

This paper examines the effectiveness of neural network algorithms for hydraulic system
fault detection and a novel neural network architecture is suggested. The proposed gated …