To facilitate the personalized smart manufacturing paradigm with cognitive automation
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …

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 …

Abstract Deep Reinforcement Learning has made significant progress in multi-agent
systems in recent years. The aim of this review article is to provide an overview of recent …

The emergence of new services and applications in emerging wireless networks (eg,
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …

Abstract Systems and machines undergo various failure modes that result in machine health
degradation, so maintenance actions are required to restore them back to a state where they …

In the context of Industry 4.0, companies understand the advantages of performing
Predictive Maintenance (PdM). However, when moving towards PdM, several …

The manufacturing world is subject to ever-increasing cost optimization pressures.
Maintenance adds to cost and disrupts production; optimized maintenance is therefore of …

Nowadays, modern engineering systems require sophisticated maintenance strategies to
ensure their correct performance. Maintenance has become one of the most important tasks …

The smart factory is at the heart of Industry 4.0 and is the new paradigm for establishing
advanced manufacturing systems and realizing modern manufacturing objectives such as …

This paper investigates the joint optimization of maintenance and spare part ordering from
multiple suppliers for systems consisting of multiple components. When components …