AI for Lean

Program Content & Structure

1. Introduction to AI and Lean

• Lean Principles Refresher:
  • Value, Value Stream, Flow, Pull, Perfection
  • Identifying and Eliminating Waste (DOWNTIME/TIMWOODS)
  • Continuous Improvement (Kaizen)
• Fundamentals of AI:
  • Machine Learning (Supervised, Unsupervised, Reinforcement)
  • Deep Learning
  • Natural Language Processing (NLP)
  • Computer Vision
• The Synergy between AI and Lean:
  • How AI amplifies Lean principles
  • Overcoming limitations of traditional Lean with AI

• Process Automation:
  • Robotic Process Automation (RPA) for repetitive tasks
  • Intelligent automation for complex workflows
  • Streamlining value streams with AI

• Predictive Analytics:
  • Forecasting demand and optimizing inventory
  • Predicting equipment failures and maintenance needs
  • Identifying bottlenecks and process variations
• Defect Detection and Quality Control:
  • Computer vision for automated visual inspection
  • Machine learning for anomaly detection
  • Improving product quality and reducing defects
• Continuous Improvement with AI:
  • Data-driven root cause analysis
  • AI-powered solutions for Kaizen events
  • Optimizing process parameters with machine learning

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