Explain how AI converts plant and supply-chain data into fewer defects, less downtime, and smarter asset use
Map AI opportunities across design, production, maintenance, and logistics in the manufacturing value chain
Distinguish core building blocks—machine learning, computer vision, optimization, and generative AI—and their data needs
Outline a five-step path from KPI definition and data mapping to deployment, monitoring, and SOP updates
Describe proven use cases in predictive maintenance, vision-based quality, and scheduling or process optimization
Identify role changes, required skills, common pitfalls, and practical adoption steps for shop-floor AI
Who this course is for
Manufacturing leaders, process and quality engineers, maintenance planners, and operations supervisors who work with plant systems (PLC, SCADA, MES, ERP) and want practical AI literacy. Basic familiarity with factory KPIs and production workflows is helpful; no prior AI expertise required.
