A Data-Based Certification Approach for Additively Manufactured Metal Aircraft Components

The aviation industry is changing towards more sustainable production, maintenance and operation of aircraft. In addition, new and diversified aircraft are being developed. Additive manufacturing is a suitable way of meeting the resulting requirements. Due to the many process parameters of additive manufacturing, which determine the component properties, certification for aviation is challenging. A digitalized process in the form of a platform is therefore presented for the certification of metallic, additively manufactured aircraft components. A key component is a new approach for data-based quality assurance. This takes into account all data available during the manufacturing process, such as design, production and post-treatment data. Machine learning algorithms are used to predict the resulting component properties. They are trained using the results of non-destructive and destructive tests. The test specimens required for this were manufactured from AlSi10Mg using the LPBF process. Data-based quality assurance in a productive environment only requires non-destructive analysis and process data to assess component quality. This gives all parties involved easy access to the digital certification process, including the innovative, data-based quality assurance process. Services required as part of the certification process can be triggered via the platform and results data (e.g. analysis results) can be processed digitally.

Presentation language: GER