To provide direction and advice for future research on Industry 4.0 maintenance, we
conducted a comprehensive analysis of 344 eligible journal papers published between …

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

Research background: The article explores the integration of Artificial Intelligence (AI) in
predictive maintenance (PM) within Industrial Internet of Things (IIoT) context. It addresses …

This paper presents an up-to-date review of data-driven condition monitoring of industrial
equipment with the focus on three commonly used equipment: motors, pumps, and bearings …

Induction machines (IMs) are utilized in different industrial sectors such as manufacturing,
transportation, transmission, and energy due to their ruggedness, low cost, and high …

The article presents a case study applying industrial artificial intelligence to Condition-Based
Maintenance in a wooden piece manufacturing company. The study focuses on the …

This article aims to present the structure and the workflow of a new software DeMa (Decision
Support Software and Database for Wellfield Management), to support wellfield managers in …

The advancements in the Internet of Things (IoT) and Machine Learning (ML) have enabled
significant improvements in Predictive Maintenance (PdM) in industries, providing economic …

The implementation of artificial intelligence and 4.0 technologies helps business leaders
make better decisions to reduce costs, improve team performance, and increase …

Anomaly detection in manufacturing pipelines remains a critical challenge, intensified by the
complexity and variability of industrial environments. This paper introduces AssemAI, an …