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 …
Learning team-based navigation: a review of deep reinforcement learning techniques for multi-agent pathfinding
Multi-agent pathfinding (MAPF) is a critical field in many large-scale robotic applications,
often being the fundamental step in multi-agent systems. The increasing complexity of MAPF …
often being the fundamental step in multi-agent systems. The increasing complexity of MAPF …
A review of AI and machine learning contribution in business process management (process enhancement and process improvement approaches)
Purpose The significance of business processes has fostered a close collaboration between
academia and industry. Moreover, the business landscape has witnessed continuous …
academia and industry. Moreover, the business landscape has witnessed continuous …
A Review of AI and Machine Learning Contribution in Predictive Business Process Management (Process Enhancement and Process Improvement Approaches)
Purpose-The significance of business processes has fostered a close collaboration between
academia and industry. Moreover, the business landscape has witnessed continuous …
academia and industry. Moreover, the business landscape has witnessed continuous …
A mathematical model for simultaneous personnel shift planning and unrelated parallel machine scheduling
This paper addresses a production scheduling problem derived from an industrial use case,
focusing on unrelated parallel machine scheduling with the personnel availability constraint …
focusing on unrelated parallel machine scheduling with the personnel availability constraint …
[PDF][PDF] Human-Centered Intelligent Monitoring and Control of Industrial Systems: A Framework for Immersive Cyber-Physical Systems
T Charter - 2024 - dspace.library.uvic.ca
This thesis embarks on a comprehensive exploration of modern industrial workplaces,
delving into the intricate interplay between humans, machines, and software. Motivated by …
delving into the intricate interplay between humans, machines, and software. Motivated by …
Demystifying Reinforcement Learning in Production Scheduling via Explainable AI
D Fischer, HM Hüsener, F Grumbach… - arXiv preprint arXiv …, 2024 - arxiv.org
Deep Reinforcement Learning (DRL) is a frequently employed technique to solve
scheduling problems. Although DRL agents ace at delivering viable results in short …
scheduling problems. Although DRL agents ace at delivering viable results in short …
FORLAPS: An Innovative Data-Driven Reinforcement Learning Approach for Prescriptive Process Monitoring
We present a novel 5-step framework called Fine-Tuned Offline Reinforcement Learning
Augmented Process Sequence Optimization (FORLAPS), which aims to identify optimal …
Augmented Process Sequence Optimization (FORLAPS), which aims to identify optimal …
On The Effectiveness Of Bottleneck Information For Solving Job Shop Scheduling Problems Using Deep Reinforcement Learning
C Waubert de Puiseau, L Zey, M Demir… - ESSN: 2701 …, 2023 - repo.uni-hannover.de
Job shop scheduling problems (JSSPs) have been the subject of intense studies for
decades because they are often at the core of significant industrial planning challenges and …
decades because they are often at the core of significant industrial planning challenges and …
Exploring the Potential of the Machine Learning Techniques in the Water Quality Assessment: A Review of Applications and Performance
FPG Márquez, AHS Al-taie, YA Zakur… - International Conference …, 2024 - Springer
In this review, the application of machine learning (ML) algorithms in water environment
research is proficiently explored. The quick increase in data size related to the water …
research is proficiently explored. The quick increase in data size related to the water …