Industrial maintenance strategies increasingly rely on artificial intelligence to predict asset
conditions and prescribe maintenance actions. The related maintenance software and …

Manufacturing ecosystems that are real-time, smart, transparent, and self-reliant are the goal
of the 4th industrialized renaissance (Industry 4.0). Industry 4.0 relies heavily on a well …

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

This paper provides a comprehensive literature review on Predictive Maintenance (PdM)
with emphasis on system architectures, purposes and approaches. In industry, any outages …

Recent technological advancements such as IoT and Big Data have granted industries
extensive access to data, opening up new opportunities for integrating artificial intelligence …

The production systems are affected by degradations and failures caused by operational
and environmental conditions. Indeed, unplanned, unscheduled maintenance (UUM) …

This article aims to review the literature on condition-based maintenance (CBM) by
analyzing various terms, applications, and challenges. CBM is a maintenance technique that …

An unprecedented growth of the industrial sector, has led to an exponential increase in the
amount of industrial IoT (IIoT) data. This is sprouting increased interest in the data-driven …

Artificial intelligence (AI) has been increasingly applied to condition-based maintenance
(CBM), a knowledge-based method taking advantage of human expertise and other system …

A precise prediction of the health status of industrial equipment is of significant importance to
determine its reliability and lifespan. This prediction provides users information that is useful …