Скачать или смотреть Part 2: AI Based Visual Inspection - Addressing Preconceptions

In this deep-dive webinar, Zetamotion addresses one of the most overlooked challenges in quality inspection: defect consensus. Do you really need to define every defect parameter in advance to use AI-based visual inspection? Spoiler: you don’t.

Join us as we explore how Spectron enables manufacturers to start with minimal input and resolve ambiguity over time—unlocking scalable, consistent, and automated inspection across your supply chain.

🔍 What you'll learn:

1. Why trying to “perfectly define” all QC parameters up front slows down AI adoption
2. How defect definitions vary between inspectors, teams, and supply chain partners
3. How Spectron helps establish a shared source of truth using consistent scans
4. Real-world use cases and how operators can fine-tune inspections using visual segment options

📌 Timestamps:
0:00 – Welcome & overview
13:00 – The misconception: “You must define all QC parameters before starting”
17:00 – What is the defect consensus problem?
22:00 – Why manual inspection leads to inconsistency
25:00 – How Spectron uses standard scans + visual segmentation to solve this
29:00 – Case study: coated panels for aviation
36:00 – Q&A: multi-site inspection, defect discovery, human vs machine consistency

📞 Learn more at https://zetamotion.com
📽️ Demo videos and resources available on request

🔗 Connect with the hosts

🔗 Michael Kurzewski (Zetamotion)
👉   / michael-kurzewski-31aaa61b3  
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🔗 Dr. Wilhelm Klein (Zetamotion)
👉   / wilhelm-e-j-klein-a717a7166  

#AIInspection #MachineVision #SyntheticData #QualityControl #industrialautomation #industrialai #automatedsolutions