The accuracy of fault diagnosis is an important indicator to ensure the reliability of key
equipment systems. Ensemble learning integrates different weak learning methods to obtain …

Additive Manufacturing (AM)(known as 3D printing) has modernised traditional
manufacturing processes by enabling the layer-by-layer fabrication of complex geometries …

The industry has embraced digitalisation leading to a greater reliance on models derived
from data. Understanding and getting insights into the models generated by machine …

The necessity to produce intricate components results in considerable progress in
manufacturing methods. Additive manufacturing (AM) is a disruptive technology that allows …

In the digital age, the digital twin eliminates physical barriers and risks, facilitating seamless
activities in both real and virtual worlds. In the context of additive manufacturing, testing 3D …

This systematic literature review employs the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …

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

As the manufacturing industry advances with sensor integration and automation, the opaque
nature of deep learning models in machine learning poses a significant challenge for fault …

The industry 4.0 is leveraging digital technologies and machine learning techniques to
connect and optimize manufacturing processes. Central to this idea is the ability to transform …

Abstract In Internet of Things networks (loT), accurate monitoring data delivery without
interruptions is vital, especially for high-risk use cases, such as in the industrial field. Existing …