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Course Outline

Course Program

Module 1: Fundamentals of AI and Machine Learning
•    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 provides a practical and strategic perspective on how to implement Artificial Intelligence solutions in manufacturing environments.
It is aimed at companies seeking to apply AI for predictive maintenance, production optimization, quality improvement, and material planning. The training sessions are delivered live by expert instructors.
 

Available Formats:
- Online with live instructor (1 to 10 participants) 
- Onsite at your facilities (1 to 15 participants)
 

Upon completing this training, participants will be able to:
•    Identify viable AI use cases in their plant
•    Assess 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 time).

Target Audience
•    Process engineers
•    Maintenance engineers
•    Quality staff
•    Production leaders
•    IT and innovation teams
 

 21 Hours

Number of participants


Price per participant

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