Edge AI in Industrial Automation

• An understanding of AI and machine learning concepts
• Experience with industrial automation systems
• Basic programming skills (Python recommended)

Audience

• Industrial engineers
• Manufacturing professionals
• AI developers

Edge AI in Industrial Automation focuses on the application of Edge AI in manufacturing and industrial settings. This course covers predictive maintenance, quality control, and process optimization using AI techniques, providing practical knowledge for enhancing industrial operations through Edge AI.

This instructor-led, live training (online or onsite) is aimed at intermediate-level industrial engineers, manufacturing professionals, and AI developers who wish to implement Edge AI solutions in industrial automation.

By the end of this training, participants will be able to:

• Understand the role of Edge AI in industrial automation.
• Implement predictive maintenance solutions using Edge AI.
• Apply AI techniques for quality control in manufacturing processes.
• Optimize industrial processes using Edge AI.
• Deploy and manage Edge AI solutions in industrial environments.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Edge AI in Industrial Automation

• Overview of Edge AI and its applications in industry
• Benefits and challenges of using Edge AI in industrial settings
• Case studies of successful Edge AI applications in manufacturing

Setting Up the Edge AI Environment

• Installing and configuring Edge AI tools
• Setting up industrial sensors and data collection systems
• Introduction to relevant Edge AI frameworks and libraries
• Hands-on exercises for environment setup

Predictive Maintenance with Edge AI

• Introduction to predictive maintenance
• Developing AI models for equipment health monitoring
• Implementing real-time fault detection and prediction
• Hands-on exercises for predictive maintenance

Quality Control Using Edge AI

• Overview of quality control in manufacturing
• AI techniques for defect detection and classification
• Implementing vision-based quality control systems
• Hands-on exercises for quality control applications

Process Optimization with Edge AI

• Introduction to process optimization
• Using AI for real-time process monitoring and control
• Implementing AI-driven decision-making systems
• Hands-on exercises for process optimization

Deploying and Managing Edge AI Solutions

• Deploying AI models on industrial edge devices
• Monitoring and maintaining Edge AI systems
• Troubleshooting and optimizing deployed models
• Hands-on exercises for deployment and management

Tools and Frameworks for Industrial Edge AI

• Overview of tools and frameworks (e.g., TensorFlow Lite, OpenVINO)
• Using TensorFlow Lite for industrial AI applications
• Hands-on exercises with optimization tools

Real-World Applications and Case Studies

• Review of successful industrial Edge AI projects
• Discussion of industry-specific use cases
• Hands-on project for building and optimizing a real-world industrial AI application

Summary and Next Steps