I'm extremely excited to announce that Siemens and AIT Austrian Institute of Technology—two leaders in industrial innovation—chose TDengine as the time-series backbone for a groundbreaking project at TCG Unitech GmbH! Here’s the magic: Imagine stitching together over a thousand time-series signals per machine with domain knowledge, and connecting it all through an intelligent semantic layer. With TDengine capturing high-frequency sensor data, PostgreSQL holding production context, and Ontopic virtualizing everything into a cohesive knowledge graph—this isn’t just data collection. It’s an orchestration that reveals hidden patterns, powers real-time anomaly and defect detection, supports traceability, and enables explainable root-cause analysis. And none of this works without good semantics. The system understands the relationships—between sensors, machines, processes, and defects—which means both AI and humans can ask the right questions and get meaningful, actionable answers. For me, this is the future of smart manufacturing: when data, infrastructure, and domain expertise come together, you get proactive, explainable, and scalable insights that keep factories running at peak performance. It's a true pleasure working with Stefan B. from Siemens AG Österreich, Stephan Strommer and David Gruber from AIT, Peter Hopfgartner from Ontopic and our friends Klaus Neubauer, Herbert Kerbl, Bernhard Schmiedinger from TCG on this technical blog! We hope this will bring some good insights into how time-series data and semantics can transform the operations of modern manufacturing! Read the full case study: https://lnkd.in/gtuf8KzU