Case Study: Autodesk Technology Centers, Boston achieves real-time machine monitoring and machine-learning anomaly detection with Tulip

Unlocking Insights with Simple Sensors and Machine Learning at the Autodesk Technology Centers, Boston

Autodesk Technology Centers, Boston operates a shared woodshop and laser/cnc facilities supporting many users, and faced challenges gaining visibility into a mix of analog and custom equipment while also training diverse, less-experienced operators. Partnering with Tulip, they used the new Edge IO device, Tulip apps and Node-RED flows plus simple vibration and current sensors to capture machine-level data and surface operational events.

Tulip implemented Edge IO sensor integrations and no-code Tulip apps to stream high-speed time-series and frequency data to the cloud, run on-device processing, and train a simple machine learning anomaly detector. The solution powers real-time dashboards, email and in-app alerts (for example, when a dust collector bin fills or a CNC mill shows anomalous vibration), enables predictive condition monitoring, speeds response and troubleshooting, and gives instructors data-driven feedback to accelerate user training — all delivered via Tulip’s platform and scalable through the AWS cloud.

Autodesk Technology Centers

Josh Aigen

Workshop Supervisor