Over the past few years, the adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies has increased substantially across a variety of industries, particularly manufacturing. As a result of these developments, conventional manufacturing procedures have been transformed, resulting in enhanced efficiency, output, and quality.
The objective of this special issue is to investigate the most recent advancements, implementations, and obstacles associated with the incorporation of AI and ML methods in manufacturing settings.
We extend an invitation to practitioners, researchers, and engineers to submit novel research articles, review papers, and case studies that cover a wide range of subjects. These may include, but are not limited to the following:
- Automation and optimization of manufacturing processes through AI
- Predictive maintenance and quality control via machine learning algorithms
- Real-time monitoring and analytics for intelligent manufacturing
- Adaptive manufacturing systems to facilitate mass customization and personalization
- AI-assisted decision support systems and human-robot collaboration
- Cyber-physical systems and digital twins in manufacturing
- Practical applications and case studies of AI and ML in the manufacturing sector
- Challenges and prospective developments in the adoption of AI and ML in manufacturing
Novel contributions, innovative methodologies, and significant insights that advance the state of the art in AI and ML applications within manufacturing contexts should be included in the submissions. Every submission will be subjected to a thorough peer review process to ascertain its superior quality and pertinence to the theme of the special issue.
This special issue offers an avenue for scholars and professionals in the field to distribute their most recent discoveries, exchange optimal methodologies, and encourage cooperation to progress further with AI and ML in the manufacturing sector. We strongly encourage submissions that make valuable contributions to the collective comprehension and implementation of these revolutionary technologies as they continue to mould the future of manufacturing.
Keywords:
Machining, Smart manufacturing, IIOT, Machine Learning, Deep learning, Condition Monitoring, Maintenance, Collaborative Robots
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Over the past few years, the adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies has increased substantially across a variety of industries, particularly manufacturing. As a result of these developments, conventional manufacturing procedures have been transformed, resulting in enhanced efficiency, output, and quality.
The objective of this special issue is to investigate the most recent advancements, implementations, and obstacles associated with the incorporation of AI and ML methods in manufacturing settings.
We extend an invitation to practitioners, researchers, and engineers to submit novel research articles, review papers, and case studies that cover a wide range of subjects. These may include, but are not limited to the following:
- Automation and optimization of manufacturing processes through AI
- Predictive maintenance and quality control via machine learning algorithms
- Real-time monitoring and analytics for intelligent manufacturing
- Adaptive manufacturing systems to facilitate mass customization and personalization
- AI-assisted decision support systems and human-robot collaboration
- Cyber-physical systems and digital twins in manufacturing
- Practical applications and case studies of AI and ML in the manufacturing sector
- Challenges and prospective developments in the adoption of AI and ML in manufacturing
Novel contributions, innovative methodologies, and significant insights that advance the state of the art in AI and ML applications within manufacturing contexts should be included in the submissions. Every submission will be subjected to a thorough peer review process to ascertain its superior quality and pertinence to the theme of the special issue.
This special issue offers an avenue for scholars and professionals in the field to distribute their most recent discoveries, exchange optimal methodologies, and encourage cooperation to progress further with AI and ML in the manufacturing sector. We strongly encourage submissions that make valuable contributions to the collective comprehension and implementation of these revolutionary technologies as they continue to mould the future of manufacturing.
Keywords:
Machining, Smart manufacturing, IIOT, Machine Learning, Deep learning, Condition Monitoring, Maintenance, Collaborative Robots
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.