Digital Twin - Self-Learning Automated Manufacturing for Sustainable Process Chain Optimization (DT-SLAM-Sustainable PCO)

• Applicant: Professor Dr.-Ing. Berend Denkena
• Subject Area: Metal-Cutting and Abrasive Manufacturing Engineering
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 547350657

The project focuses on the development of a digital twin including a self-optimising model for component manufacturing to improve fatigue life and promote sustainability. The aim is to create a numerical process chain model that efficiently adjusts surface and subsurface properties to optimise fatigue behavior. The project focuses on experimental investigation of process chains, evaluation of energy consumption and development of predictive models. The combination of experimental findings and modelled data will create a digital twin for resource and energy efficiency.

• DFG Programme: Research Grants
• International Connection: Brazil
• Partner Organisation: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; (CAPES); Setor bancario Norte
• Cooperation Partners: Professor Dr.-Ing. Alexandre Mendes Abrão; Professor Dr.-Ing. Carlos Eiji Hirata Ventura