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Course Outline
Day 1: 09:00 - 16:00 (7h)
The Fundamentals of Artificial Intelligence
- Defining AI, machine learning, and deep learning.
- Learning paradigms: supervised, unsupervised, and reinforcement.
- Dispelling myths and understanding the reality of AI in industry.
AI in the Smart Manufacturing Context
- Characteristics that define a “smart” factory.
- The role of AI in Industry 4.0 and industrial automation.
- An overview of enabling technologies (IoT, edge computing, digital twins).
Primary Manufacturing Use Cases
- Predictive maintenance and equipment reliability.
- Quality assurance and anomaly detection.
- Process optimization and yield enhancement.
Navigating the Data Lifecycle
- Sensing and gathering industrial data.
- Data preparation and quality management.
- Foundational concepts in data-driven decision-making.
Day 2: 09:00 - 16:00 (7h)
AI Project Strategy and Planning
- Identifying high-impact application areas.
- Assembling the appropriate team and defining success metrics.
- Addressing common challenges and mitigation tactics.
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 Implementation
- Steps for initiating an AI initiative.
- Technology considerations and vendor selection.
- Scalability, ethics, and workforce adaptation.
Summary and Future Steps
Requirements
- Familiarity with basic industrial processes or plant operations.
- Interest in digital transformation or innovation strategy.
- Openness to 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
