Big Data and Machine Learning Applications for Material Removal, Additive and Hybrid Manufacturing Processes
A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).
Deadline for manuscript submissions: 31 October 2025 | Viewed by 36
Special Issue Editor
Interests: intelligent manufacturing; machinability of materials; optimization methodologies; CNC machining; CAD/CAM/CAE systems
Special Issue Information
Dear Colleagues,
The paradigm of intelligent manufacturing processes is undergoing a major evolution worldwide.
Big Data Analytics (BDA) and machine learning algorithms (MLA), along with artificial intelligence (AI), constitute vital attributes for supporting industrial automation, quality control, digital transformation, data-driven manufacturing, and process optimization.
Big Data comprises broader and perplexed data groups that conventional data processing frameworks fail to handle beneficially. Machine learning algorithms fall into the general category of artificial intelligence, where robust and game-changing infrastructures enable real-time equipment performance, predictive analytics, and process optimization.
Intelligent manufacturing, Big Data, and machine learning constitute key enablers for establishing the foundations for developing and implementing promising solutions related to manufacturing integration that can balance the trade-off between high productivity and exceptional quality.
CNC technology continues to see service in manufacturing sectors worldwide, whereas new technologies like additive and hybrid manufacturing seem to be quite promising from the perspective of producing sophisticated, versatile products and processing new materials with advanced properties. Therefore, current research in academia and industry focuses on experimental studies concerning the exploitation of the applicability of Big Data and machine learning systems to advanced manufacturing technologies.
This Special Issue’s goal is to disseminate the most recent findings in research while providing readers and scholars a forum for the mutual exchange of concepts, opinions, and ideas related but not limited to the advances in manufacturing process automation; the application of neural networks for correlating process-related variables with different performance metrics/objectives; ad hoc interfaces for profitable design and manufacturing; intelligent process modeling and simulation; application of meta-heuristic algorithms for process optimization; Big Data analytics with emphasis to machinability attributes (i.e., material removal rate, surface integrity, and tool life); and intelligent manufacturing systems.
Dr. Nikolaos A. Fountas
Guest Editor
Manuscript Submission Information
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Keywords
- predictive analytics in manufacturing
- cloud computing
- metaheuristics/intelligent algorithms
- process optimization
- systems interaction
- neural networks
- digital manufacturing
- smart manufacturing systems
- data-driven materials processing
- CAD-CAM-CNC
- robotics and automation
- supply chain management
- process modeling and simulation
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