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Course Outline
Day 1: 09:00 - 16:00 (7h)
Foundations of Artificial Intelligence
- Defining AI, machine learning, and deep learning
- Learning paradigms: supervised, unsupervised, and reinforcement
- Distinguishing myths from realities of AI in industry
AI within Smart Manufacturing
- Defining the characteristics of a “smart” factory
- AI’s contribution to Industry 4.0 and industrial automation
- Overview of supporting technologies (IoT, edge computing, digital twins)
Significant Manufacturing Use Cases
- Predictive maintenance and enhancing equipment reliability
- Quality assurance and anomaly detection techniques
- Process optimization and yield enhancement
The Data Lifecycle Explained
- Sensing and gathering industrial data
- Data preparation and addressing quality considerations
- Fundamental concepts in data-driven decision making
Day 2: 09:00 - 16:00 (7h)
AI Project Planning and Strategic Approach
- Identifying high-impact use cases
- Assembling the right team and defining success metrics
- Addressing common challenges and mitigation strategies
Case Studies and Industry Applications
- Real-world examples from automotive, food, pharma, and heavy industries
- Insights gained from digital transformation journeys
- Key success factors and common pitfalls to avoid
Roadmap for Implementation
- Steps for initiating an AI initiative
- Technology considerations and vendor selection processes
- Scalability, ethical considerations, and workforce adaptation
Summary and Future Steps
Requirements
- Familiarity with fundamental industrial processes or plant operations
- An interest in digital transformation or innovation strategy
- Comfort in discussing technology adoption
Target Audience
- Operations managers
- Plant executives
- Technical leads
14 Hours
Testimonials (2)
All in general
Daniele Donzelli - ITT ITALIA S.r.l.
Course - CANoe for CAN Compact Training
PLC basic knowledge
