Dr.-Ing. Florian Stamer

Dr.-Ing. Florian Stamer

Area of Research:

  • Intelligent Quality Control Loops
  • In-Process Integration of Sensors
  • Industry 4.0 with Focus on Networking and Data Exchange
  • Dynamic quality control in the context of circular production

 

General Tasks:

  • Coordination of the lecture Production Integrated Metrology

  • Coordination and management of the quality assurance team

  • Coordination and management of the junior research group "Dynamic Quality Control for the Sustainable Production of Mobility Solutions” ICM

  • Lernfabrik Globale Produktion

 

Projects:

  • ReKoNeT: Collaboration in Value Networks Based on Industry 4.0
  • SmartCoNet - Smart Control of Customer-Based Collaborative Manufacturing Networks with Secured Transparency
  • BaSys4SupplyQ – BaSys4.0 for Horizontal Integration
  • BaSys4ServiceNet – Platform based Quality Data Exchange across Companies 

 

Curriculum Vitae:

since 07/2023 Junior research group leader „Dynamic Quality Control for the Sustainable Production of Mobility Solutions“
07/2022 Doctorate in engineering “Dynamic Pricing in Multi-Variant Production: An Adaptive Approach Using Reinforcement Learning”
since 01/2022 Team leader “Quality Assurance”
since 12/2017 Research Associate at the Institute of Production Science (wbk) at Karlsruhe Institute of Technology (KIT)
2010 - 2017 Business Engineering student at RWTH Aachen

 

Publications


Effect of technology multiplier: A framework for analysis of innovation perspectives on production segment allocation
Stamer, F.; Girke, R.; Yang, S.; Chun, J.-H.; Lanza, G.
2024. CIRP Journal of Manufacturing Science and Technology, 55, 272–291. doi:10.1016/j.cirpj.2024.10.002
A Quality Data Model Based on Asset Administration Shell Technology to Enable Autonomous Quality Control Loops
Bilen, A.; Stamer, F.; Behrendt, S.; Lanza, G.
2024. Production at the Leading Edge of Technology : Proceedings of the 13th Congress of the German Academic Association for Production Technology (WGP), Freudenstadt, November 2023. Ed.: T. Bauernhansl, 195–204, Springer Nature Switzerland. doi:10.1007/978-3-031-47394-4_20
Analysis and evaluation of adaptive remanufacturing strategies for mechanical products; [Analyse und Bewertung von adaptiven Remanufacturing-Strategien für mechanische Produkte]
Stamer, F.; Fabig, F.
2024. at - Automatisierungstechnik, 72 (9), 884 – 892. doi:10.1515/auto-2024-0007
Influencing Residual Stress in PBF-LB/M Processes Through In-Process Microstructure Assessment and Selective Laser Heat Treatment
Groenewold, J.; Hammes, J.; Stamer, F.; Lanza, G.
2024. J. J. Beaman, D. Kovar, M. Cullinan, Z. Sha, R. Crawford & M. Tilton (Eds.), Proceedings of the 35th Annual International SOLID FREEFORM FABRICATION SYMPOSIUM 2024 Hrsg.: Beaman, Joseph J.; Kovar, Desiderio; Cullinan, Michael; Sha, Zhenghui; Crawford, Rich; Tilton, Maryam, 1027–1035
Adaptive acquisition planning for visual inspection in remanufacturing using reinforcement learning
Kaiser, J.-P.; Gäbele, J.; Koch, D.; Schmid, J.; Stamer, F.; Lanza, G.
2024. Journal of Intelligent Manufacturing. doi:10.1007/s10845-024-02478-0
Enhancing Visual Inspection in Remanufacturing: A Reinforcement Learning Approach with Integrated Robot Simulation
Koch, D.; Kaiser, J.-P.; Stamer, F.; Stark, R.; Lanza, G.
2024. doi:10.5445/IR/1000176932
Optimizing quality and cost in remanufacturing under uncertainty – A novel optimization framework utilizing quality and process modelling
Stamer, F.; Sauer, J.
2024. Production Engineering. doi:10.1007/s11740-024-01314-x
Selective disassembly planning considering process capability and component quality utilizing reinforcement learning
Tabar, R. S.; Magnanini, M. C.; Stamer, F.; May, M. C.; Lanza, G.; Wärmefjord, K.; Söderberg, R.
2024. Procedia CIRP, 121, 1 – 6. doi:10.1016/j.procir.2023.09.221
CT-Messungen automatisieren - Ein Konzept zur Nutzung von Reinforcement Learning zur Parametrisierung von CT-Messungen
Blum, E.; Stamer, F.; Lanza, G.
2023. wt Werkstattstechnik online, 113 (11-12), 545–549. doi:10.37544/1436-4980-2023-11-12-81
Towards a Service-Oriented Architecture for Production Planning and Control: A Comprehensive Review and Novel Approach
Behrendt, S.; Stamer, F.; May, M. C.; Lanza, G.
2023. Proceedings of the 5th Conference on Production Systems and Logistics (CPSL-2). Ed.: D. Herberger, 255–267, publish-Ing. doi:10.15488/15271
A development approach for a standardized quality data model using asset administration shell technology in the context of autonomous quality control loops for manufacturing processes
Bilen, A.; Stamer, F.; May, M. C.; Lanza, G.
2023. Conference Proceedings : 23rd International Conference & Exhibition, 1–4, Euspen
Evolutionary cost-tolerance optimization for complex assembly mechanisms via simulation and surrogate modeling approaches: application on micro gears
Khezri, A.; Schiller, V.; Goka, E.; Homri, L.; Etienne, A.; Stamer, F.; Dantan, J.-Y.; Lanza, G.
2023. The International Journal of Advanced Manufacturing Technology, 126 (9-10), 4101–4117. doi:10.1007/s00170-023-11360-x
Dynamic pricing of product and delivery time in multi-variant production using an actor critic reinforcement learning
Stamer, F.; Lanza, G.
2023. CIRP Annals. doi:10.1016/j.cirp.2023.04.019
Experiment data for the application of actor critic reinforcement learning for dynamic pricing in production
Stamer, F.
2023, April 5. doi:10.5445/IR/1000157568
Concept for In-process Measurement of Residual Stress in AM Processes by Analysis of Structure-Borne Sound
Groenewold, J.; Stamer, F.; Lanza, G.
2023. Production at the Leading Edge of Technology. Ed.: M. Liewald, 24–31, Springer International Publishing. doi:10.1007/978-3-031-18318-8_3
Machine Learning in Manufacturing towards Industry 4.0: From ‘For Now’ to ‘Four-Know’
Chen, T.; Sampath, V.; May, M. C.; Shan, S.; Jorg, O. J.; Aguilar Martín, J. J.; Stamer, F.; Fantoni, G.; Tosello, G.; Calaon, M.
2023. Applied Sciences (Switzerland), 13 (3), Art.-Nr.: 1903. doi:10.3390/app13031903
Development of a simulative approach in order to estimate the impact of smart services on a production system – Linking the influence of smart services to economic potential in production
Stamer, F.; Fausel, K.; Peukert, S.; Lanza, G.
2023. Production Engineering. doi:10.1007/s11740-023-01185-8
Identification of hybridization strategies for combining fused filament fabrication with unidirectional tape reinforcement
Matkovic, N.; Höger, K.; Friedmann, M.; Stamer, F.; Fleischer, J.; Lanza, G.
2023. Composites Communications, 38, Art.Nr. 101484. doi:10.1016/j.coco.2022.101484
Modeling the effect of workpiece temperature on micromagnetic high-speed-3MA-testing in case of AISI 4140
Güray, A.; Böttger, D.; González, G.; Stamer, F.; Lanza, G.; Wolter, B.; Schulze, V.
2023. Procedia CIRP, 117, 133 – 138. doi:10.1016/j.procir.2023.03.024
Dynamische Lieferzeit-Preisgestaltung in variantenreicher Produktion : Ein adaptiver Ansatz mithilfe von Reinforcement Learning. PhD dissertation
Stamer, F.
2022, October 27. Shaker Verlag. doi:10.5445/IR/1000151540
Successful Collaboration in Global Production Networks - fair, secured, connected
Silbernagel, R.; Stamer, F.; Sautter, B.
2022, April 1. (G. Lanza, Ed.), wbk Institut für Produktionstechnik
Erfolgreiche Kollaboration in Produktionsnetzwerken - fair, sicher, vernetzt
Silbernagel, R.; Stamer, F.
2022, March 15. (G. Lanza & C. Weinhardt, Eds.), wbk Institut für Produktionstechnik
Application of a Dynamic Pricing for Variant Manufacturing in Production Networks using Reinforcement Learning - Result Data
Stamer, F.
2022, January 5. doi:10.5445/IR/1000141615
Adaptive and Dynamic Feedback Loops between Production System and Production Network based on the Asset Administration Shell
Stamer, F.; Maier, S.; Peukert, S.; Lanza, G.
2022. Procedia CIRP, 15th CIRP Conference on Intelligent Computation in ManufacturingEngineering, 14-16 July 2021, Ed.: R. Teti, 112, 79–84. doi:10.1016/j.procir.2022.09.048
Identifying Digitalization Trends in Global Production Networks - A Python Data Mining Tool
Reichert, F.; Stamer, F.; Klenk, F.
2021, October 18. doi:10.5445/IR/1000136718
Recommender Systems for Capability Matchmaking
Badewitz, W.; Stamer, F.; Linzbach, J.; Dann, D.; Weinhardt, C.; Lichtenberger, S.
2021. 2021 IEEE 23rd Conference on Business Informatics: CBI 2021 ; Virtual Conference, 1–3 September 2021 ; Volume 2 – CBI Forum and Workshop Papers. Ed.: J. P. A. Almeida, 87–96, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CBI52690.2021.10059
Deriving Collaboration Cases in Production Networks Considering Smart Services
Stamer, F.; Bizenberger, P.; Häfner, B.; Lanza, G.
2020. 8th CIRP Global Web Conference – Flexible Mass Customisation (CIRPe 2020). Ed.: K. Kellens, 33–38, Elsevier. doi:10.1016/j.procir.2021.01.048
Using smart services as a key enabler for collaboration in global production networks
Stamer, F.; Steinke, M.; Silbernagel, R.; Häfner, B.; Lanza, G.
2020. 53rd CIRP Conference on Manufacturing Systems (CIRP CMS), July 1-3, 2020, online, 730–735, Elsevier. doi:10.1016/j.procir.2020.04.065
Kollaboration in globalen Wertschöpfungsnetzwerken : Datenbasierte Regelung kollaborativer Wertschöpfungsnetzwerke mittels geschützter Transparenz
Silbernagel, R.; Stamer, F.; Häfner, B.; Linzbach, J.; Lanza, G.
2019. ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, 114 (5), 314–317. doi:10.3139/104.112085
Next Level Production Networks
Friedli, T.; Schuh, G.; Lanza, G.; Remling, D.; Gützlaff, A.; Stamer, F.
2019. Zeitschrift für wirtschaftlichen Fabrikbetrieb, 114 (3), 101–104. doi:10.3139/104.112057
Framework for Smart Services as a premise for collaboration in the era of manufacturing services = Framework für Smart Services als Grundlage für Kollaboration im Kontext aufkommender industrieller Dienstleistungen
Stamer, F.; Labbouz, A.; Haefner, B.; Lanza, G.
2019. Production at the leading edge of technology : Proceedings of the 9th Congress of the German Academic Association for Production Technology (WGP), September 30th - October 2nd, Hamburg 2019. Ed.: J. P. Wulfsberg, 603–612, Springer Vieweg. doi:10.1007/978-3-662-60417-5_60