Deep reinforcement learning in smart manufacturing: A review and prospects
To facilitate the personalized smart manufacturing paradigm with cognitive automation
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …
A review of cooperative multi-agent deep reinforcement learning
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 …
systems in recent years. The aim of this review article is to provide an overview of recent …
[HTML][HTML] Envisioning maintenance 5.0: Insights from a systematic literature review of Industry 4.0 and a proposed framework
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 …
conducted a comprehensive analysis of 344 eligible journal papers published between …
Applications of distributed machine learning for the Internet-of-Things: A comprehensive survey
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) …
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
[HTML][HTML] Multi-agent deep reinforcement learning based Predictive Maintenance on parallel machines
In the context of Industry 4.0, companies understand the advantages of performing
Predictive Maintenance (PdM). However, when moving towards PdM, several …
Predictive Maintenance (PdM). However, when moving towards PdM, several …
Reinforcement learning for predictive maintenance: A systematic technical review
The manufacturing world is subject to ever-increasing cost optimization pressures.
Maintenance adds to cost and disrupts production; optimized maintenance is therefore of …
Maintenance adds to cost and disrupts production; optimized maintenance is therefore of …
Reinforcement and deep reinforcement learning-based solutions for machine maintenance planning, scheduling policies, and optimization
O Ogunfowora, H Najjaran - Journal of Manufacturing Systems, 2023 - Elsevier
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 …
degradation, so maintenance actions are required to restore them back to a state where they …
Applications of Reinforcement Learning for maintenance of engineering systems: A review
AP Marugán - Advances in Engineering Software, 2023 - Elsevier
Nowadays, modern engineering systems require sophisticated maintenance strategies to
ensure their correct performance. Maintenance has become one of the most important tasks …
ensure their correct performance. Maintenance has become one of the most important tasks …
Modeling agent decision and behavior in the light of data science and artificial intelligence
Agent-based modeling (ABM) has been widely used in numerous disciplines and practice
domains, subject to many eulogies and criticisms. This article presents key advances and …
domains, subject to many eulogies and criticisms. This article presents key advances and …
A review of the applications of multi-agent reinforcement learning in smart factories
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 …
advanced manufacturing systems and realizing modern manufacturing objectives such as …