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Duration 14 hours
Course Outline
Day 1: 09:00 - 16:00 (7h)
Fundamentals of Artificial Intelligence
- Defining AI, machine learning, and deep learning
- Learning paradigms: supervised, unsupervised, and reinforcement
- Distinguishing myths from reality in industrial AI
AI in the Context of Smart Manufacturing
- Defining the 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)
Principal Applications in Manufacturing
- Predictive maintenance and enhancing equipment reliability
- Quality assurance and anomaly detection
- Process optimization and yield improvement
Understanding the Data Lifecycle
- Sensing and gathering industrial data
- Data preparation and quality assurance
- 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 appropriate team and defining success metrics
- Addressing common challenges and mitigation strategies
Case Studies and Industry Applications
- Practical examples from automotive, food, pharma, and heavy industries
- Insights gained from digital transformation journeys
- Key success factors and potential pitfalls
Roadmap for Implementation
- Steps for launching an AI initiative
- Technology considerations and vendor selection
- Scalability, ethics, and workforce adaptation
Summary and Next Steps
Requirements
- Familiarity with fundamental industrial processes or plant operations
- Interest in digital transformation or innovation strategy
- Openness to discussions regarding technology adoption
Audience
- Operations managers
- Plant executives
- Technical leads
Testimonials (2)
How to use and explore AI for daily works
Giovani Natalia - PT Astra Honda Motor
Course - AI for Supply Chain and Manufacturing Logistics
All in general
