TY - CONF A1 - Fabry, Cagtay A1 - Hirthammer, Volker A1 - Pittner, Andreas A1 - Rethmeier, Michael T1 - WelDX - a file format for processing and archiving welding research data N2 - The talk gives an introduction into gas metal arc welding and its relation to plasma science as well as current challenges in welding research concerning research data management and the application of the FAIR principles. The WelDX project is introduced and the main goals are discussed and contrasted with the current features of the weldx API. Different internal and public facing use cases focusing on research data management and their implementation using weldx are presented. The interactive part of the presentation displays some advanced multi layer use cases and data analysis using the weldx API as well as the integration of materials properties into weldx. T2 - International Workshop on FAIR Data in Plasma Science CY - Online meeting DA - 16.05.2022 KW - WelDX KW - Open science KW - Research data management KW - Arc welding KW - Digital transformation PY - 2022 AN - OPUS4-55153 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Fabry, Cagtay A1 - Hirthammer, Volker A1 - Scherer, Martin K. A1 - Pittner, Andreas A1 - Rethmeier, Michael T1 - Multi-Layer welding data analysis and open data approach using WelDX N2 - The talk motivates and introduces the WelDX project and the proposed solutions for current challenges in the field of research data management and Open Science practices in welding research. Using an exemplary welding dataset based on the joint and welding process design of offshore structures, advanced data fusion and analysis capabilities are demonstrated. The dataset shown consists of a complex welding sequence covering multiple weld layers with varying process parameters and adaptive weaving motions to cover manufacturing tolerances. In the presentation, an interactive exploration of the dataset contents in the spatial domain is presented. Furthermore, transformation between spatial and time domain of the data is demonstrated. In addition to data gathered during the welding process, the integration of downstream testing data and results is also explained. For demonstration, integration of weld seam cross section images and Vickers hardness mapping test results into the dataset are explained an demonstrated. The testing data is set into context with the welding process information. Finally, implications for advancements in research data management for WAAM and AI applications are discussed. T2 - The 75th IIW Annual Assembly and International Conference CY - Tokyo, Japan DA - 17.07.2022 KW - WelDX KW - Research data management KW - Open science KW - Arc welding KW - Digital transformation PY - 2022 AN - OPUS4-55354 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -