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Duration 14 hours
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 learning
- Dispelling myths and clarifying the realities of AI in industry
AI in the Context of Smart Manufacturing
- Defining the attributes of a “smart” factory
- The role of AI in Industry 4.0 and industrial automation
- An overview of enabling technologies (IoT, edge computing, digital twins)
Key Use Cases in Manufacturing
- Predictive maintenance and enhancing equipment reliability
- Quality assurance and anomaly detection
- Process optimization and improving yield
Understanding the Data Lifecycle
- Collecting and sensing industrial data
- Data preparation and quality management considerations
- Foundational concepts in data-driven decision-making
Day 2: 09:00 - 16:00 (7h)
AI Project Planning and Strategy
- Identifying high-impact application areas
- Assembling the right team and defining success metrics
- Addressing common challenges and mitigation strategies
Case Studies and Industry Applications
- Real-world examples from automotive, food, pharmaceutical, and heavy industries
- Insights gained from digital transformation journeys
- Key success factors and pitfalls to avoid
Roadmap for Getting Started
- Steps for launching an AI initiative
- Technical considerations and vendor selection
- Scalability, ethical considerations, and workforce adaptation
Summary and Next Steps
Requirements
- Familiarity with fundamental industrial processes or plant operations
- An interest in digital transformation or innovation strategies
- Openness to discussions on adopting new technologies
Target 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
