DynaSty: Predictive Dynamic Stability for “green” heavy-duty Milling of aeroengine component: towards environmentally benign and sustainable production
| Reference number | |
| Coordinator | Lunds universitet - Lunds Tekniska Högskola Inst f maskinvetenskaper |
| Funding from Vinnova | SEK 2 750 935 |
| Project duration | August 2025 - August 2028 |
| Status | Ongoing |
| Venture | Advanced digitalization - Industrial needs-driven innovation |
| Call | Advanced digitalization - Industrial innovation 2025 |
Purpose and goal
The project combines classical stability analysis with AI to optimize heavy-duty milling, enhancing stability, efficiency, and eco-friendliness.
Expected effects and result
This project focuses on developing innovative, sustainable solutions to detect, identify, and predict both tool-induced and workpiece-induced instabilities in rough milling, especially for complex aero-engine components. A key objective is to improve machining efficiency and surface quality by using advanced green cooling and lubrication strategies, such as MQL, Cryo-MQL, and supercritical CO₂.
Planned approach and implementation
The approach includes the development of a predictive sensor-based monitoring system that leverages feature extraction and process optimization to improve stability. The project will evaluate how process parameters and lubrication conditions affect machinability, stability, tool life, and surface integrity.