Uni Siegen Logo
Bild Automatisierung
PROTECH Institutslogo

Benjamin Heinbach, M.Sc. M.Sc.

Sprechzeiten:
nur nach Vereinbarung


xing
linkedin
orcid
google_schoolar
research_gates

Publikationen

  • Heinbach, B., Burggräf, P., Wagner, J. : Deep reinforcement learning for layout planning–An MDP-based approach for the facility layout problem (2023) in: Manufacturing Letters. https://doi.org/10.1016/j.mfglet.2023.09.007 Original
  • Heinbach, B., Burggräf, P., Wagner, J. : gym-flp: A Python Package for Training Reinforcement Learning Algorithms on Facility Layout Problems (2023) in: . https://doi.org/10.21203/rs.3.rs-371586/v1 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., Dannapfel, M., Wagner, J., Heinbach, B., Föhlsch, N., Dackweiler, J. : “ReLIFE”: Business Models for Data-Based Remanufacturing: Adaptive Remanufacturing for Life Cycle Optimisation of Networked Capital Goods (2023) in: The Monetization of Technical Data: Innovations from Industry and Research. https://doi.org/10.1007/978-3-662-66509-1_28 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., Dannapfel, M., Wagner, J., Heinbach, B., T., Föhlisch, N., Dackweiler, J. : „ReLIFE“: Geschäftsmodelle zum datenbasierten Remanufacturing: Adaptives Remanufacturing zur Lebenszyklusoptimierung vernetzter Investitionsgüter (2021) in: Monetarisierung von technischen Daten (pp.559-573). http://dx.doi.org/10.1007/978-3-662-62915-4_28 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
  • 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., Heinbach, B. : Bibliometric Study on the Use of Machine Learning as Resolution Technique for Facility Layout Problems (2021) in: IEEE Access (Volume: 9). 10.1109/ACCESS.2021.3054563 Download Original
  • Burggräf, P., Wagner, J., Heinbach, B., Wigger, M. : Design of a Methodological Framework for Adaptive Remanufacturing-based Business Models (2021) in: Procedia CIRP, Volume 98, Pages 547-552. 10.1016/j.procir.2021.01.149 Download Original
  • Burggräf, P., Wagner, J., Koke, B., Bamberg, M. : Performance assessment methodology for AI-supported decision-making in production management (2020) in: Procedia CIRP, Volume 93. 10.1016/j.procir.2020.03.047 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
  • Burggräf, P., Wagner, J., Dannapfel, M., Fluchs, S., Müller, K., Koke, B. : Survey based dataset on automation decisions for assembly systems in Germany (2020) in: Data in Brief, Available online 29 May 2020. 10.1016/j.dib.2020.105782
  • Koke, B., Moehler, Robert C. : Earned Green Value management for project management: A systematic review (2019) in: Journal of Cleaner Production (2019), S. 180-197.
  • Burggräf, P., Wagner, J., Dannapfel, M., Fluchs, S., Müller, K., Koke, B. : Automation decisions in flow-line assembly systems based on a cost-benefit analysis (2019) in: S ScienceDirect, 52nd CIRP Conference on Manufacturing Systems, 2019, S.529-534. 10.1016/j.procir.2019.03.150
  • Burggräf, P., Wagner, J., Koke, B., Manoharan, K. : Sensor retrofit for a coffee machine as condition monitoring and predictive maintenance use case (2019) in: Ludwig, T., Pipek, V. (Hrsg): Tagungsband - 14. Internationale Tagung Wirtschaftsinformatik, 2019, S. 62-66. Download
  • Burggräf, P., Wagner, J., Dannapfel, M., Müller, K., Koke, B. : Multivariable Automatisierungsentscheidungen - Tool zur Aufwand- und Nutzenbewertung als Entscheidungsgrundlage (2019) in: wt-online, Ausgabe 3, 2019 , S. 134-139. Original
  • Burggräf, P., Wagner, J., Koke, B. : Artificial intelligence in production management: A review of the current state of affairs and research trends in academia (2018) in: International Conference on Information Management and Processing (ICIMP), 12-14 January 2018, London, United Kingdom, IEEE (2018) pp.82-88.

Benjamin Heinbach, M.Sc. M.Sc.

Sprechzeiten:
nur nach Vereinbarung


xing
linkedin
orcid
google_schoolar
research_gates

Publikationen

  • Heinbach, B., Burggräf, P., Wagner, J. : Deep reinforcement learning for layout planning–An MDP-based approach for the facility layout problem (2023) in: Manufacturing Letters. https://doi.org/10.1016/j.mfglet.2023.09.007 Original
  • Heinbach, B., Burggräf, P., Wagner, J. : gym-flp: A Python Package for Training Reinforcement Learning Algorithms on Facility Layout Problems (2023) in: . https://doi.org/10.21203/rs.3.rs-371586/v1 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., Dannapfel, M., Wagner, J., Heinbach, B., Föhlsch, N., Dackweiler, J. : “ReLIFE”: Business Models for Data-Based Remanufacturing: Adaptive Remanufacturing for Life Cycle Optimisation of Networked Capital Goods (2023) in: The Monetization of Technical Data: Innovations from Industry and Research. https://doi.org/10.1007/978-3-662-66509-1_28 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., Dannapfel, M., Wagner, J., Heinbach, B., T., Föhlisch, N., Dackweiler, J. : „ReLIFE“: Geschäftsmodelle zum datenbasierten Remanufacturing: Adaptives Remanufacturing zur Lebenszyklusoptimierung vernetzter Investitionsgüter (2021) in: Monetarisierung von technischen Daten (pp.559-573). http://dx.doi.org/10.1007/978-3-662-62915-4_28 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
  • 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., Heinbach, B. : Bibliometric Study on the Use of Machine Learning as Resolution Technique for Facility Layout Problems (2021) in: IEEE Access (Volume: 9). 10.1109/ACCESS.2021.3054563 Download Original
  • Burggräf, P., Wagner, J., Heinbach, B., Wigger, M. : Design of a Methodological Framework for Adaptive Remanufacturing-based Business Models (2021) in: Procedia CIRP, Volume 98, Pages 547-552. 10.1016/j.procir.2021.01.149 Download Original
  • Burggräf, P., Wagner, J., Koke, B., Bamberg, M. : Performance assessment methodology for AI-supported decision-making in production management (2020) in: Procedia CIRP, Volume 93. 10.1016/j.procir.2020.03.047 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
  • Burggräf, P., Wagner, J., Dannapfel, M., Fluchs, S., Müller, K., Koke, B. : Survey based dataset on automation decisions for assembly systems in Germany (2020) in: Data in Brief, Available online 29 May 2020. 10.1016/j.dib.2020.105782
  • Koke, B., Moehler, Robert C. : Earned Green Value management for project management: A systematic review (2019) in: Journal of Cleaner Production (2019), S. 180-197.
  • Burggräf, P., Wagner, J., Dannapfel, M., Fluchs, S., Müller, K., Koke, B. : Automation decisions in flow-line assembly systems based on a cost-benefit analysis (2019) in: S ScienceDirect, 52nd CIRP Conference on Manufacturing Systems, 2019, S.529-534. 10.1016/j.procir.2019.03.150
  • Burggräf, P., Wagner, J., Koke, B., Manoharan, K. : Sensor retrofit for a coffee machine as condition monitoring and predictive maintenance use case (2019) in: Ludwig, T., Pipek, V. (Hrsg): Tagungsband - 14. Internationale Tagung Wirtschaftsinformatik, 2019, S. 62-66. Download
  • Burggräf, P., Wagner, J., Dannapfel, M., Müller, K., Koke, B. : Multivariable Automatisierungsentscheidungen - Tool zur Aufwand- und Nutzenbewertung als Entscheidungsgrundlage (2019) in: wt-online, Ausgabe 3, 2019 , S. 134-139. Original
  • Burggräf, P., Wagner, J., Koke, B. : Artificial intelligence in production management: A review of the current state of affairs and research trends in academia (2018) in: International Conference on Information Management and Processing (ICIMP), 12-14 January 2018, London, United Kingdom, IEEE (2018) pp.82-88.

 
© Universität Siegen | Datenschutzerklärung | E-Mail an die Webredaktion