Sensors, vital elements in data acquisition systems, play a crucial role in various industries.
However, their exposure to harsh operating conditions makes them vulnerable to faults that …

A systematic review on interpretability research of intelligent fault diagnosis models Page 1
Measurement Science and Technology ACCEPTED MANUSCRIPT A systematic review on …

Maintenance strategies are vital for industrial and manufacturing systems. This study
considers a proactive maintenance strategy and emphasizes using analytics and data …

This study presents an efficient vibration-based fault detection method for rotating machines
utilising the poly-coherent composite spectrum (pCCS) and machine learning techniques …

This study presents a prescriptive analytics framework for optimal intelligent predictive
maintenance of railway tracks. We use machine learning and Graph Convolutional Networks …

The last-mile logistics in cities have become an indispensable part of the urban logistics
system. This study aims to explore the effective selection of last-mile logistics nodes to …

Rolling bearings are critical components of industrial equipment, and predicting their
remaining useful life (RUL) is a challenging task. This article proposes a new end-to-end …

Machine learning (ML) techniques are increasingly used to diagnose faults in aerospace
applications, but diagnosing multiple faults in aircraft fuel systems (AFSs) remains …

The integration of human knowledge and experience with artificial intelligence, especially in
the context of Industry5. 0, holds the promise of advanced capabilities for manufacturing that …

Within the modern industry, the analysis and critical evaluation of existing techniques for the
detection, prevention, and monitoring of industrial equipment are essential aspects for …