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 …
Reinforcement learning applied to production planning and control
The objective of this paper is to examine the use and applications of reinforcement learning
(RL) techniques in the production planning and control (PPC) field addressing the following …
(RL) techniques in the production planning and control (PPC) field addressing the following …
Trustworthy reinforcement learning against intrinsic vulnerabilities: Robustness, safety, and generalizability
A trustworthy reinforcement learning algorithm should be competent in solving challenging
real-world problems, including {robustly} handling uncertainties, satisfying {safety} …
real-world problems, including {robustly} handling uncertainties, satisfying {safety} …
[HTML][HTML] Artificial Intelligence in manufacturing: State of the art, perspectives, and future directions
Inspired by the natural intelligence of humans and bio-evolution, Artificial Intelligence (AI)
has seen accelerated growth since the beginning of the 21st century. Successful AI …
has seen accelerated growth since the beginning of the 21st century. Successful AI …
A review of deep reinforcement learning approaches for smart manufacturing in industry 4.0 and 5.0 framework
A del Real Torres, DS Andreiana, Á Ojeda Roldán… - Applied Sciences, 2022 - mdpi.com
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 …
This work presents the status and the potential for the I4. 0 and I5. 0's revolutionary …
A review on learning to solve combinatorial optimisation problems in manufacturing
An efficient manufacturing system is key to maintaining a healthy economy today. With the
rapid development of science and technology and the progress of human society, the …
rapid development of science and technology and the progress of human society, the …
A deep reinforcement learning based hyper-heuristic for modular production control
In nowadays production, fluctuations in demand, shortening product life-cycles, and highly
configurable products require an adaptive and robust control approach to maintain …
configurable products require an adaptive and robust control approach to maintain …
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 …
{AWARE}: Automate workload autoscaling with reinforcement learning in production cloud systems
Workload autoscaling is widely used in public and private cloud systems to maintain stable
service performance and save resources. However, it remains challenging to set the optimal …
service performance and save resources. However, it remains challenging to set the optimal …
Pixel‐level thin crack detection on road surface using convolutional neural network for severely imbalanced data
T Siriborvornratanakul - Computer‐Aided Civil and …, 2023 - Wiley Online Library
Because roads are the major backbone of the transportation network, research about crack
detection on road surfaces has been popular in computer and infrastructure engineering …
detection on road surfaces has been popular in computer and infrastructure engineering …