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

Predictive maintenance is an essential aspect of microgrid operations as it enables
identifying potential equipment failures in advance, reducing downtime, and increasing the …

This paper examines the integration of Industry 5.0 principles with advanced predictive
maintenance (PdM) and condition monitoring (CM) practices, based on Industry 4.0's …

In this review, the industry's current issues regarding intelligent manufacture are presented.
This work presents the status and the potential for the I4. 0 and I5. 0's revolutionary …

While attracting increasing research attention in science and technology, Machine Learning
(ML) is playing a critical role in the digitalization of manufacturing operations towards …

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 …

The distributed assembly flow shop scheduling (DAFS) problem has received much
attention in the last decade, and a variety of metaheuristic algorithms have been developed …

There is a growing interest in implementing artificial intelligence for operations research in
the industrial environment. While numerous classic operations research solvers ensure …

Multi-agent reinforcement learning (MARL) is a widely used Artificial Intelligence (AI)
technique. However, current studies and applications need to address its scalability, non …

Optimizing condition-based maintenance (CBM) strategies based on machine learning (ML)
methods as reinforcement learning (RL) have been receiving increasing attention due to …