Artificial Intelligence Applications for Industry 4.0
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".
Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 4784
Special Issue Editors
Interests: scheduling; uncertainty; Industry 4.0
Interests: image processing; binary tomography; discrete tomography; image analysis
Interests: data science; human–computer interaction; natural language processing; spatial ability; virtual reality
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the advent of new technologies brought about by Industry 4.0, the complexity of production systems continues to increase to ensure a high degree of adaptability, flexibility, reconfigurability and robustness. The importance of flexibility largely determines the ability of a system to effectively deal with a variety of uncertainties and their consequences. Artificial Intelligence solutions are one of the most important technologies that can ensure this flexibility. In the continuously changing environment, AI methods can be used to provide the autonomous work of units, generate optimal schedules, minimize energy consumption, recognize faults, etc.
This Special Issue aims to present AI approaches in smart factories, especially in the field of sustainability. Researchers in this field are invited to contribute their original, unpublished works. Both research and review papers are welcome. Topics of interest include, but are not limited to:
- AI and sustainable infrastructure;
- AI and green transportation;
- AI and additive manufacturing;
- Decision-support systems, including evolutionary algorithms, swarm intelligence, etc.;
- Deep learning;
- Neural networks;
- Fuzzy systems;
- Architectures, methods, and approaches for distributed AI systems;
- Image processing, pattern recognition, and speech recognition;
- AI and responsible consumption;
- Practical applications with the aforementioned approaches in industry, such as case studies or benchmarking.
Dr. Tibor Holczinger
Dr. Judit Szűcs
Dr. Tibor Guzsvinecz
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence
- Industry 4.0
- smart factory
- sustainability