Course Outline
Course Program
Module 1: AI and Machine Learning Fundamentals
• Key concepts
• Model types
• Industrial use cases
Module 2: Predictive Maintenance
• Anomaly detection
• Supervised models
• Interpreting results
Module 3: Production Optimization
• OEE analysis
• Bottleneck detection
• Resource optimization
Module 4: Quality Analytics
• Defect prediction
• CAPA analysis
• Risk assessment
Module 5: Implementation Roadmap
• Data architecture
• Project phases
• ROI measurement
Requirements
General Information
This course offers a practical and strategic perspective on how to implement Artificial Intelligence solutions in manufacturing environments.
It is designed for companies seeking to apply AI for predictive maintenance, production optimization, quality improvement, and material planning. The trainings are conducted live by expert instructors.
Available modalities:
- Online with live instructor (1 to 10 participants)
- In-person at your facilities (1 to 15 participants)
Upon completion of this training, participants will be able to:
• Identify viable AI use cases in their plant
• Evaluate data availability and quality
• Apply basic industrial prediction models
• Design an initial implementation roadmap
Duration
21 hours (3 days of 7 hours each, including breaks and meal times).
Target Audience
• Process Engineers
• Maintenance Engineers
• Quality Staff
• Production Leaders
• IT and Innovation Teams