Publikationen

Sauer, R., Burggraef, P., Steinberg, F. : Bridging human expertise and machine learning in production management: a case study on ML-based decision support systems to prevent missing parts at assembly (2024) in: Production Engineering. 10.1007/s11740-024-01306-x Original

Burggraef, P., Steinberg, F., Sauer, R., Nettesheim, P. : Machine learning implementation in small and medium-sized enterprises: insights and recommendations from a quantitative study (2024) in: Production Engineering. 10.1007/s11740-024-01274-2 Original

Burggraef, P., Steinberg, F., Diebel, M., Becher, A., Sauer, R., Baeck, L., Wigger, M., Germann, N. : Enhancing Resource Efficiency And Monetization In Metal Recycling Through Supply Chain-Wide Digitalization: An Approach For Single-Variety Metal Stream Optimization And CO2 Reduction (2024) in: 6th Conference on Production Systems and Logistics. 10.15488/17761 Original

Burggraef, P., Steinberg, F., Sauer, R., Nettesheim, P., Wigger, M., Becher, A., Greiff, K., Spies, A.M., Köhler, H., Huesmann, R., Atapin, A., Kaufeld, S., Krolle, A., Faul, A., Winter, J., Küppers, B., Ludes, A. : Boosting the Circular Manufacturing of the Sustainable Paper Industry - A First Approach to Recycle Paper from Unexploited Sources such as Lightweight Packaging, Residual and Commercial Waste (2024) in: 56th CIRP Conference on Manufacturing Systems. 10.1016/j.procir.2023.09.027 Original

Burggräf, P., Steinberg, F., Becher, A., Sauer, R., Wigger, M. : Towards a Sustainable Industrial Society–Critical Capabilities for the Transformation to a Circular Economy in Manufacturing Companies (2024) in: WGP 2023: Production at the Leading Edge of Technology. https://doi.org/10.1007/978-3-031-47394-4_30 Original

Burggräf, P., Adlon, T., Steinberg, F., Salzwedel, J., Nettesheim, P., Tschauder, H. : Transforming Food Production: Smart Containers for Sustainable and Transparent Food Supply Chains (2023) in: APMS 2023: Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures. https://doi.org/10.1007/978-3-031-43688-8_34 Original

Burggräf, P., Steinberg, F., Weißer, T., Radisic-Aberger, O. : Deciding on when to change–a benchmark of metaheuristic algorithms for timing engineering changes (2023) in: International Journal of Production Research. 10.1080/00207543.2023.2226778 Original

Steinberg, F., Burggräf, P., Wagner, J., Heinbach, B., Saßmannshausen, T., Brintrup, A. : A novel machine learning model for predicting late supplier deliveries of low-volume-high-variety products with application in a German machinery industry (2023) in: Supply Chain Analytics. https://doi.org/10.1016/j.sca.2023.100003 Original

Burggräf, P., Steinberg, F., Nettesheim, P., Vedder, M., Kolter, G. : Cyber-Physical Optimization of Production Processes Using Two AIs: A Robot-Guided MAG Welding Use-Case (2023) in: 16th CIRP Conference on Intelligent Computation in Manufacturing Engineering. https://doi.org/10.1016/j.procir.2023.06.152 Original

Burggräf, P., Steinberg, F., Adlon, T., Nettesheim, P., Salzwedel, J. : Bridging data gaps in the food industry – sensor-equipped metal food containers as an enabler for sustainability (2023) in: Proceedings of the Conference on Production Systems and Logistics. https://doi.org/10.15488/13488 Original

Burggräf, P., Steinberg, F., Adlon, T., Nettesheim, P., Kahmann, H., Wu, L. : Smart Containers—Enabler for More Sustainability in Food Industries? (2022) in: WGP 2022: Production at the Leading Edge of Technology. https://doi.org/10.1007/978-3-031-18318-8_43 Original

Burggräf, P., Steinberg, F., Heinbach, B., Bamberg, M. : Reinforcement Learning for Process Time Optimization in an Assembly Process Utilizing an Industry 4.0 Demonstration Cell (2022) in: Procedia CIRP. 107. 1095-1100. 10.1016/j.procir.2022.05.114 Original

Burggräf, P., Wagner, J., Steinberg, F., Heinbach, B., Wigger, M., Saßmannshausen, T. : Life Cycle Assessment for Adaptive Remanufacturing: incorporating ecological considerations into the planning of maintenance activities – a case study in the German heavy machinery industry (2022) in: Procedia CIRP. 105. 320-325. 10.1016/j.procir.2022.02.053 Original

Burggräf, P., Wagner, J., Heinbach, B., Steinberg, F., Perez, A., Schmallenbach, L., Garcke, J., Steffes-lai, D., Wolter, M. : Predictive analytics in quality assurance for assembly processes: lessons learned from a case study at an industry 4.0 demonstration cell (2021) in: Procedia CIRP. 10.36227/techrxiv.14113715.v3 Original

Burggräf, P., Wagner, J., Heinbach, B., Steinberg, F. : Machine Learning-Based Prediction of Missing Components for Assembly – a Case Study at an Engineer-to-Order Manufacturer (2021) in: IEEE Access (Volume 9). 10.1109/ACCESS.2021.3075620 Original

Saßmannshausen, T., Burggräf, P., Wagner, J., Hassenzahl, M., Heupel, T., Steinberg, F. : Trust in artificial intelligence within production management – an exploration of antecedents (2021) in: Ergonomics, S. 1-18. https://doi.org/10.1080/00140139.2021.1909755 Original

Burggräf, P., Wagner J., Heinbach, B., Steinberg, F., Pérez, A., Schmallenbach, L., Garcke, J., Steffes-Iai, D., Wolter, M. : Predictive analytics in quality assurance for assembly processes: lessons learned from a case study at an industry 4.0 demonstration cell (2021) in: TechRxiv. https://dx.doi.org/10.36227/techrxiv.14113715.v3 Original

Burggräf, P., Wagner, J., Koke, B., Steinberg, F. : Approaches for the prediction of lead times in an engineer to order environment - a systematic review (2020) in: IEEE Access. 10.1109/ACCESS.2020.3010050 Download