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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
- Clarifying myths versus realities of AI in industry
AI in the Context of Smart Manufacturing
- Defining characteristics of a “smart” factory
- The role of AI in Industry 4.0 and industrial automation
- Overview of enabling technologies (IoT, edge computing, digital twins)
Key Manufacturing Use Cases
- Predictive maintenance and equipment reliability
- Quality assurance and anomaly detection
- Process optimization and yield enhancement
Understanding the Data Lifecycle
- Sensing and acquiring industrial data
- Data preparation and quality factors
- Fundamental concepts in data-driven decision making
Day 2: 09:00 - 16:00 (7h)
AI Project Planning and Strategy
- Identifying high-impact use cases
- Assembling the right team and defining success metrics
- Common challenges and risk mitigation strategies
Case Studies and Industry Applications
- Real-world examples from automotive, food, pharma, and heavy industries
- Insights from digital transformation journeys
- Key success factors and pitfalls to avoid
Roadmap for Getting Started
- Steps for initiating an AI project
- Technology considerations and vendor selection
- Scalability, ethics, and workforce adaptation
Summary and Next Steps
Requirements
- Basic knowledge of industrial processes or plant operations
- Interest in digital transformation or innovation strategy
- Familiarity with discussions on 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
