Abstract: AuToWin aims to develop and deploy an advanced Digital Twin tool leveraging automated machine learning (AutoML) to optimize predictive maintenance for manufacturing partners. Led by Dakik Yazılım and IOTIQ, together with automotive part manufacturer ERMETAL as the industry partner, the project will build upon the AuToWin Digital Twin platform to integrate real-time sensor data streaming from ERMETAL’s presses and use AutoML pipelines to automatically train models for anomaly detection, lifetime estimation, and failure prediction. Over 9 months, the solution will be tested and validated on ERMETAL’s production lines to achieve TRL7. Key objectives include reducing equipment downtime and failures through optimized maintenance planning, and decreasing maintenance costs through condition-based monitoring. Upon project completion, AuToWin will provide a user-friendly and interoperable Digital Twin solution empowering data-driven decision-making for optimized production workflows and sustainable operational excellence in manufacturing environments.