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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
- Dispelling myths and clarifying realities of AI in industry
AI in the Context of Smart Manufacturing
- What defines a factory as “smart”?
- AI’s contribution to Industry 4.0 and industrial automation
- An overview of enabling technologies (IoT, edge computing, digital twins)
Key Use Cases in Manufacturing
- Predictive maintenance and ensuring equipment reliability
- Quality assurance and identifying anomalies
- Process optimisation and enhancing yield
Navigating the Data Lifecycle
- Sensing and gathering industrial data
- Data preparation and quality benchmarks
- Foundational concepts in data-driven decision making
Day 2: 09:00 - 16:00 (7h)
AI Project Planning and Strategy
- Pinpointing 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 the automotive, food, pharmaceutical, and heavy industries
- Insights gained from digital transformation journeys
- Key success factors and pitfalls to avoid
Roadmap for Getting Started
- Steps for launching an AI initiative
- Technology considerations and vendor selection
- Scalability, ethics, and workforce adaptation
Summary and Next Steps
Requirements
- A foundational understanding of basic industrial processes or plant operations
- An interest in digital transformation or innovation strategy
- Familiarity with discussions regarding technology adoption
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
