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Course Outline
Day 1: 09:00 - 16:00 (7h)
Basics of Artificial Intelligence
- Defining AI, machine learning, and deep learning
- Learning paradigms: supervised, unsupervised, and reinforcement
- Dispelling myths and clarifying AI's role in industry
AI Within Smart Manufacturing Frameworks
- Characteristics that define a "smart" facility
- AI's contribution to Industry 4.0 and industrial automation
- Supporting technologies overview (IoT, edge computing, digital twins)
Critical Manufacturing Applications
- Predictive maintenance and equipment dependability
- Quality assurance and detecting anomalies
- Optimizing processes and enhancing yield
Navigating the Data Lifecycle
- Capturing and gathering industrial data
- Data preprocessing and quality metrics
- Foundational concepts for data-informed decisions
Day 2: 09:00 - 16:00 (7h)
Planning and Strategy for AI Projects
- Pinpointing high-value use cases
- Assembling the right team and defining success KPIs
- Addressing common obstacles and mitigation tactics
Case Studies and Sectoral Applications
- Real-world instances from automotive, food, pharma, and heavy industries
- Insights from digital transformation experiences
- Key success drivers and potential pitfalls to steer clear of
Initial Roadmap for Implementation
- Procedures for launching an AI initiative
- Technological factors and vendor selection criteria
- Scalability, ethical considerations, and workforce adaptation
Recap and Future Directions
Requirements
- Familiarity with fundamental industrial workflows or plant operations
- Curiosity regarding 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
