Resource-efficient design of fatigue-resistant product by digital tools and innovative manufacturing

Purpose and goal

The feasibility study addresses the need for new digital tools for well-informed decisions i the design process to accelerate development. The aim of the project is to investigate the possibility of using the Stilfold process to improve the performance of a gas turbine component with reduced waste and resource utilization through increased fatigue resistance. Additionally, the feasibility of fatigue data collected from literature using the AI-powered tool by Ferritico will be investigated.

Expected effects and result

To link product performance to material properties and manufacturing, models are needed for each step from material to finished product via manufacturing. These models may already exist, e.g. FE models describing a component, or new models as digital twins via AI. By combining these models, the entire product can be described including funding from each stage. This means that well-informed decisions can be made more quickly, which positively affects time-to-market and costs.

Planned approach and implementation

The project is divided into 4 work packages (WP). WP1: project management and making a plan for a full-scale project. WP2: proposal to redesign a gas turbine component for improved fatigue resistance via the Stilfold process. WP3: multi-source data collection strategy using Ferriticos ML-verktyg, as fatigue data is sensitive to test conditions, will be obtained and validated. WP4: experimental fatigue testing for validation and special cases.