A.6: AI REGIO Industrial Faults Predictive Maintenance (IFPM): Difference between revisions
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• '''Learning Ability''': Supervised training | • '''Learning Ability''': Supervised training | ||
• '''Related technologies''': | • '''Related technologies''': ML algorithms, Digital Twins | ||
• '''Applicable Research Area''': Collaborative AI | • '''Applicable Research Area''': Collaborative AI | ||
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• '''License Information''': Creative Commons Attribution 4.0 International License | • '''License Information''': Creative Commons Attribution 4.0 International License | ||
• '''Related to circularity and sustainability''': | • '''Related to circularity and sustainability''': Not directly | ||
• '''Audience''': Manufacturers | • '''Audience''': Manufacturers | ||
Latest revision as of 09:18, 27 December 2024
• Short Description: A data analytics module that, leveraging Machine Learning techniques, processes all the data received from shopfloor to identify potential faults.
• Reference, URL: https://www.ai4europe.eu/research/ai-catalog/ai-regio-industrial-faults-predictive-maintenance-ifpm
• Applicable Business Category: Manufacturing
• Application in relevant Projects/Initiatives: AIREGIO
• Asset Type: Executable
• AI Breadth: ML, SVM, bianary classification
• Learning Ability: Supervised training
• Related technologies: ML algorithms, Digital Twins
• Applicable Research Area: Collaborative AI
• Applicable Technical Category: AI services
• License Information: Creative Commons Attribution 4.0 International License
• Related to circularity and sustainability: Not directly
• Audience: Manufacturers
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