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Duration 14 hours
Course Outline
Day 1: 09:00 - 16:00 (7h)
The Foundations 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 Within the Framework of Smart Manufacturing
- Characteristics that define a “smart” factory
- The role of AI in Industry 4.0 and industrial automation
- Introduction to supporting technologies (IoT, edge computing, digital twins)
Critical AI Applications in Manufacturing
- Ensuring equipment reliability through predictive maintenance
- Enhancing quality assurance via anomaly detection
- Improving yield and optimizing processes
Navigating the Data Lifecycle
- Gathering and sensing industrial data
- Data preparation and maintaining data quality
- Core concepts in data-driven decision-making
Day 2: 09:00 - 16:00 (7h)
Strategy and Planning for AI Projects
- Pinpointing high-impact use cases
- Assembling the right team and defining success metrics
- Addressing common challenges with mitigation strategies
Industry Case Studies and Applications
- Practical examples from automotive, food, pharmaceutical, and heavy industries
- Key takeaways from digital transformation experiences
- Identifying success factors and common pitfalls to avoid
A Roadmap for Getting Started
- Actionable steps for launching an AI initiative
- Considerations for technology selection and vendor choice
- Ensuring scalability, ethical practice, and workforce adaptation
Recap and Future Steps
Requirements
- Familiarity with basic 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
