Transform manufacturing quality with Intelligent Jidoka, AI-powered defect detection, and predictive qualaity systems. This course is designed for learners who want to understand how artificial intelligence and machine learning can advance traditional Jidoka toward scalable, zero-defect manufacturing.

You’ll explore computer vision, convolutional neural networks, anomaly detection, transfer learning, synthetic defect generation, explainable AI, and digital twins for intelligent quality control. Learn how thermal monitoring, multimodal sensor fusion, edge AI, industrial IoT, and digital error-proofing support faster defect identification and prevention. You’ll also examine predictive quality, AI-enhanced Statistical Process Control, automated root cause analysis, self-correcting production loops, and MLOps practices for monitoring model drift and accuracy. Explore how cobots, human-AI collaboration, safety controls, and sustainable Lean AI support responsible automation. By the end of the course, you’ll be able to evaluate AI methods for defect detection, apply predictive quality approaches, improve manufacturing performance, and plan scalable, responsible AI solutions for intelligent and zero-defect manufacturing.