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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.
- Separating industry AI myths from practical realities.
AI within the Scope of Smart Manufacturing
- Defining the characteristics of a “smart” factory.
- The pivotal role of AI in Industry 4.0 and industrial automation.
- An overview of foundational technologies (IoT, edge computing, digital twins).
Prominent Applications in Manufacturing
- Predictive maintenance and enhancing equipment reliability.
- Quality assurance and identifying anomalies.
- Optimizing processes to improve yield.
Navigating the Data Lifecycle
- Capturing and gathering industrial data through sensing.
- Data preparation and critical quality factors.
- Foundational concepts in data-driven decision-making.
Day 2: 09:00 - 16:00 (7h)
AI Project Planning and Strategic Approach
- Pinpointing high-impact use cases.
- Assembling the appropriate team and defining success metrics.
- Addressing common challenges with effective mitigation strategies.
Case Studies and Sector-Specific Applications
- Practical examples from automotive, food, pharma, and heavy industries.
- Insights gained from various digital transformation journeys.
- Identifying success factors and common pitfalls to avoid.
A Roadmap for Implementation
- Key steps for initiating an AI project.
- Evaluating technology options and selecting the right vendors.
- Considering scalability, ethics, and workforce adaptation.
Recap and Future Directions
Requirements
- Familiarity with basic industrial processes or plant operations.
- A keen interest in digital transformation and innovation strategies.
- An open mindset toward technology adoption conversations.
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
