Engineer repairing a server under a lamp

[Manufacturing AI Series — Troubleshooting] 279TB Manufacturing Data Collection Troubleshooting — From Hardware Limits to Consistency Guarantees

Virtualization-Based Edge Deployment · Pub/Sub Payload Limit Workaround · Idempotency-Based Consistency Overcoming pilot site surprises and cloud limitations in MDE optimization Cloud Tech Unit · GCP Delivery SA 3 Yoon Sung-jae | 2026-02-23 Problem Definition — Engineering in the Trenches No matter how perfect an architecture diagram looks, it often falls apart in front of rack-mount servers and network cables at a manufacturing site. While the previous article covered the “elegant” architecture, this one dives into the mud-and-guts troubleshooting that field engineers had to wrestle through during the pilot phase. ...

February 26, 2026 · 9 min · Yoon Sung-jae
Data center rack with fiber optic communication equipment

[Manufacturing AI Series — Architecture] MDE Architecture Design for 279TB Collection — Building an Edge-to-Cloud Pipeline Across 8 Factories

250+ Industrial Protocols · Edge-to-Cloud Pipeline · Physical-Level Project Isolation A real-world Manufacturing Data Engine deployment balancing security and cost trade-offs Cloud Tech Unit · GCP Delivery SA 3 Yoon Sung-jae | 2026-02-23 Business Background — PINN Model-Based Convergence Data Platform In manufacturing digital transformation (DX), the biggest hurdle is the “last mile” — securely and seamlessly moving on-site IT and OT data to the cloud. This article covers a case where, as the cloud infrastructure partner for the Korean government-led “2025 PINN (Physics-Informed Neural Networks) Model Manufacturing Convergence Data Collection and Validation Project,” we built an integrated system on Google Cloud Manufacturing Data Engine (MDE) for heterogeneous data from 8 manufacturing companies. ...

February 25, 2026 · 6 min · Yoon Sung-jae