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Fabian Steinberg, M.Sc.

Büro:
CB 1.2
Sprechzeiten:
nur nach Vereinbarung


xing
linkedin
orcid
research_gates

Publikationen

  • 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

/team/images/steinberg_neu.jpg

Fabian Steinberg, M.Sc.

Büro:
CB 1.2
Sprechzeiten:
nur nach Vereinbarung


xing
linkedin
orcid
research_gates

Publikationen

  • 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

 
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