Enabling extreme data by using DS/AI approaches

conference paper Enabling extreme data by using DS/AI approaches published yes I. Gräßler author 475650000-0001-5765-971X Thomas Hesse author 76202 Jens Pottebaum author 405http://orcid.org/0000-0001-8778-2989 IrisGraessler editor 152 department Design for Assembly, Disassembly and Reassembly (DfADR) prepares for high levels of material circularity in terms of repair and remanufacturing. The intention of reassembling products and their part simplies that inspection and sorting need to be integrated with value-conserving objectives. Further, disassembly and reassembly require higher competence levels of workforce than assembly. To provide the required information during engineering, a metadata model (MDM) is required that links established product models to capability models. Since processes to be carried out for realizing a product largely determine required employees’ capabilities, the proposed approach uses the ADR process domain to connect product and capability domains. The research is based on a systematic literature analysis to identify existing approaches regarding MDMs of ADR processes. Based on the results, an integrative MDM is developed that answers defined competence questions. The model enables queries which support engineers by feedback on which skills are required for a product. This builds up a basis to check whether required skills are available in the manufacturing company, either early in product engineering or later in ADR planning. LibreCat University2026Paderborn eng 1st International Symposium on Hybrid Intelligence in Product and Production Engineering10.17619/UNIPB/1-2640 Gräßler, I., et al. “Enabling Extreme Data by Using DS/AI Approaches.” 1st International Symposium on Hybrid Intelligence in Product and Production Engineering, edited by Iris Graessler, LibreCat University, 2026, doi:<a href="https://doi.org/10.17619/UNIPB/1-2640">10.17619/UNIPB/1-2640</a>. Gräßler I, Hesse T, Pottebaum J. Enabling extreme data by using DS/AI approaches. In: Graessler I, ed. 1st International Symposium on Hybrid Intelligence in Product and Production Engineering. LibreCat University; 2026. doi:<a href="https://doi.org/10.17619/UNIPB/1-2640">10.17619/UNIPB/1-2640</a> @inproceedings{Gräßler_Hesse_Pottebaum_2026, place={Paderborn}, title={Enabling extreme data by using DS/AI approaches}, DOI={<a href="https://doi.org/10.17619/UNIPB/1-2640">10.17619/UNIPB/1-2640</a>}, booktitle={1st International Symposium on Hybrid Intelligence in Product and Production Engineering}, publisher={LibreCat University}, author={Gräßler, I. and Hesse, Thomas and Pottebaum, Jens}, editor={Graessler, Iris}, year={2026} } Gräßler, I., Hesse, T., & Pottebaum, J. (2026). Enabling extreme data by using DS/AI approaches. In I. Graessler (Ed.), 1st International Symposium on Hybrid Intelligence in Product and Production Engineering. LibreCat University. <a href="https://doi.org/10.17619/UNIPB/1-2640">https://doi.org/10.17619/UNIPB/1-2640</a> I. Gräßler, T. Hesse, and J. Pottebaum, “Enabling extreme data by using DS/AI approaches,” in 1st International Symposium on Hybrid Intelligence in Product and Production Engineering, Paderborn, 2026, doi: <a href="https://doi.org/10.17619/UNIPB/1-2640">10.17619/UNIPB/1-2640</a>. Gräßler, I., Thomas Hesse, and Jens Pottebaum. “Enabling Extreme Data by Using DS/AI Approaches.” In 1st International Symposium on Hybrid Intelligence in Product and Production Engineering, edited by Iris Graessler. Paderborn: LibreCat University, 2026. <a href="https://doi.org/10.17619/UNIPB/1-2640">https://doi.org/10.17619/UNIPB/1-2640</a>. I. Gräßler, T. Hesse, J. Pottebaum, in: I. Graessler (Ed.), 1st International Symposium on Hybrid Intelligence in Product and Production Engineering, LibreCat University, Paderborn, 2026. 666832026-08-07T11:59:52Z2026-08-07T12:05:12Z