Assembly Line

Automating Quality Machine Inspection Infused with Edge AI and Digital Twins for Device Monitoring

📅 Date:

✍️ Authors: Karunakaran Samuel, Mac Mahalingam, Raju Karuppiah, Chandra Mohan Ravanan

🔖 Topics: Manufacturing Analytics, IT OT Convergence

🏢 Organizations: AWS, Kyndryl

In this post, we will discuss an AI-based solution Kyndryl has built on Amazon Web Services (AWS) to detect pores on the welding process using acoustic data and a custom-built algorithm leveraging voltage data. We’ll describe how Kyndryl collaborated with AWS to design an end-to-end solution for detecting welding pores in a manufacturing plant using AWS analytics services and by enabling digital twins to monitor welding machines effectively.

Kyndryl’s solution flow consists of collecting acoustic data with voltage and current from welding machines, processing and inferencing data at the edge to detect welding pores while providing actionable insights to welding operators. Additionally, data is streamed to the cloud to perform historical analysis and improve operational efficiency and product quality over time. A digital twin is enabled to monitor the welding operation in real-time with warnings created to proactively manage the asset when predefined thresholds are met.

Read more at AWS Blog