Machine learning and deep learning in smart manufacturing: The smart grid paradigm
Industry 4.0 is the new industrial revolution. By connecting every machine and activity
through network sensors to the Internet, a huge amount of data is generated. Machine …
through network sensors to the Internet, a huge amount of data is generated. Machine …
Deep reinforcement learning in production systems: a systematic literature review
Shortening product development cycles and fully customisable products pose major
challenges for production systems. These not only have to cope with an increased product …
challenges for production systems. These not only have to cope with an increased product …
[HTML][HTML] Comparing different supervised machine learning algorithms for disease prediction
Supervised machine learning algorithms have been a dominant method in the data mining
field. Disease prediction using health data has recently shown a potential application area …
field. Disease prediction using health data has recently shown a potential application area …
Resource management with deep reinforcement learning
Resource management problems in systems and networking often manifest as difficult
online decision making tasks where appropriate solutions depend on understanding the …
online decision making tasks where appropriate solutions depend on understanding the …
Human-centric artificial intelligence architecture for industry 5.0 applications
Human-centricity is the core value behind the evolution of manufacturing towards Industry
5.0. Nevertheless, there is a lack of architecture that considers safety, trustworthiness, and …
5.0. Nevertheless, there is a lack of architecture that considers safety, trustworthiness, and …
Optimization of global production scheduling with deep reinforcement learning
Abstract Industrie 4.0 introduces decentralized, self-organizing and self-learning systems for
production control. At the same time, new machine learning algorithms are getting …
production control. At the same time, new machine learning algorithms are getting …
Designing an adaptive production control system using reinforcement learning
A Kuhnle, JP Kaiser, F Theiß, N Stricker… - Journal of Intelligent …, 2021 - Springer
Modern production systems face enormous challenges due to rising customer requirements
resulting in complex production systems. The operational efficiency in the competitive …
resulting in complex production systems. The operational efficiency in the competitive …
Reinforcement learning for robot research: A comprehensive review and open issues
T Zhang, H Mo - International Journal of Advanced Robotic …, 2021 - journals.sagepub.com
Applying the learning mechanism of natural living beings to endow intelligent robots with
humanoid perception and decision-making wisdom becomes an important force to promote …
humanoid perception and decision-making wisdom becomes an important force to promote …
Deep reinforcement learning for semiconductor production scheduling
Despite producing tremendous success stories by identifying cat videos [1] or solving
computer as well as board games [2],[3], the adoption of deep learning in the semiconductor …
computer as well as board games [2],[3], the adoption of deep learning in the semiconductor …
Explainable reinforcement learning in production control of job shop manufacturing system
A Kuhnle, MC May, L Schäfer… - International Journal of …, 2022 - Taylor & Francis
Manufacturing in the age of Industry 4.0 can be characterised by a high product variety and
complex material flows. The increasing individualisation of products requires adaptive …
complex material flows. The increasing individualisation of products requires adaptive …