Lean AI Manufacturing Expert (LAME)

Length: 2 Days

The Lean AI Manufacturing Expert (LAME) Certification Course by Tonex is designed to equip participants with the knowledge and skills to integrate AI technologies into manufacturing processes. This course follows lean principles to optimize production, minimize waste, and enhance overall efficiency in manufacturing operations.

Learning Objectives:

  • Understand the fundamentals of lean manufacturing principles.
  • Gain proficiency in the application of AI technologies within manufacturing contexts.
  • Learn how to identify opportunities for AI integration to streamline production processes.
  • Develop strategies to minimize waste and maximize efficiency through AI implementation.
  • Acquire hands-on experience with tools and techniques for deploying AI solutions in manufacturing environments.
  • Explore case studies and best practices for successful lean AI manufacturing implementations.

Audience: This course is ideal for manufacturing professionals, engineers, project managers, and anyone interested in leveraging AI to enhance manufacturing efficiency. Participants should have a basic understanding of manufacturing processes and technology concepts.

Course Outline:

Module 1: Introduction to Lean Manufacturing Principles

  • Overview of Lean Manufacturing
  • Principles of Waste Reduction
  • Value Stream Mapping
  • Continuous Improvement Techniques
  • Just-in-Time (JIT) Production
  • Lean Six Sigma Integration

Module 2: Overview of Artificial Intelligence Technologies in Manufacturing

  • Introduction to AI in Manufacturing
  • Types of AI Technologies (e.g., Machine Learning, Computer Vision)
  • Applications of AI in Production Planning and Scheduling
  • AI for Quality Control and Defect Detection
  • Predictive Maintenance with AI
  • Robotics and Automation in Manufacturing

Module 3: Identifying Opportunities for AI Integration in Manufacturing Processes

  • Assessment of Current Manufacturing Processes
  • Identification of Pain Points and Bottlenecks
  • Data Collection and Analysis for AI Integration
  • Risk Assessment and Feasibility Analysis
  • Stakeholder Engagement and Alignment
  • Prioritization of AI Implementation Opportunities

Module 4: Strategies for Minimizing Waste and Maximizing Efficiency with AI

  • Lean Thinking in AI Integration
  • Optimization of Production Processes with AI
  • Real-time Monitoring and Adaptive Control Systems
  • Inventory Management and Demand Forecasting with AI
  • Energy Efficiency and Resource Optimization
  • Lean Supply Chain Management with AI

Module 5: Hands-on Training: Deploying AI Solutions in Manufacturing Environments

  • Setting Up AI Infrastructure and Tools
  • Data Preprocessing and Feature Engineering
  • Model Selection and Training
  • Integration of AI Solutions into Existing Systems
  • Testing and Validation of AI Models
  • Maintenance and Continuous Improvement of AI Systems

Module 6: Case Studies and Best Practices in Lean AI Manufacturing

  • Successful Implementations of AI in Manufacturing
  • Lessons Learned from Lean AI Integration Projects
  • Case Studies from Various Industry Sectors
  • Best Practices for Sustainable Lean AI Manufacturing
  • Challenges and Pitfalls in Lean AI Implementation
  • Future Trends and Innovations in Lean AI Manufacturing