Dr.-Ing. Constantin Hofmann

Area of Research:

Coordination of the learning factory global production
Digitization in production planning, cloud computing and web technology in production
Production control of flexible production systems
Shopfloor Management
MES systems

General Tasks:

Coordination of lecture…
- MBA Hector Production Engineering
Workshop coach Lean and Industry 4.0
Coordination learning factory global production

Projects:

Innovation Center SAP – Development of an AI-based multi-agent production control for matrix production
Innovation Center SAP – Efficiency improvement of a MO-MCTS-based multi-objective optimizer for scheduling of a matrix production
AiF ShopfloorPulse

Test benches:

Lernfabrik Globale Produktion

Dissertation: Development of an AI-based multi-agent production control for matrix production

Curriculum Vitae:

05/07/1989	Born in Frankfurt am Main
10/2010-04/2014	Industrial Engineering (B.Sc.) at KIT focusing on information technology and production science
09/2012-06/2013	Génie industriel at INSA Lyon
04/2014-12/2016	Industrial Engineering (M.Sc.) at KIT
since 03/2017	Research Associate at Institute of Production Science (wbk) at Karlsruher Institute of Technology (KIT)

Publications

Wandlungsfähige Produktion für die Kreislaufwirtschaft
Beyerer, J.; Bretthauer, G.; Hofmann, C.; Lanza, G.
2022. at - Automatisierungstechnik, 70 (6), 501–503. doi:10.1515/auto-2022-0063

Agiles Produktionssystem mittels lernender Roboter bei ungewissen Produktzuständen am Beispiel der Anlasser-Demontage = Concept of an agile production system based on learning robots applied to disassembly
Lanza, G.; Asfour, T.; Beyerer, J.; Deml, B.; Fleischer, J.; Heizmann, M.; Furmans, K.; Hofmann, C.; Cebulla, A.; Dreher, C.; Kaiser, J.-P.; Klein, J.-F.; Leven, F.; Mangold, S.; Mitschke, N.; Stricker, N.; Pfrommer, J.; Wu, C.; Wurster, M.; Zaremski, M.
2022. at - Automatisierungstechnik, 70 (6), 504–516. doi:10.1515/auto-2021-0158

Automatisierung und Einsatz von Robotern im Pathologielabor = Automation and application of robotics in the pathology laboratory
Herbst, H.; Rüdiger, T.; Hofmann, C.
2022. Der Pathologe, 43 (3), 210–217. doi:10.1007/s00292-022-01073-5

Hybrid Monte Carlo tree search based multi-objective scheduling
Hofmann, C.; Liu, X.; May, M.; Lanza, G.
2022. Production Engineering, 17, 133–144. doi:10.1007/s11740-022-01152-9

Self-adjusting multi-objective scheduling based on Monte Carlo Tree Search for matrix production assembly systems
Stricker, N.; Kuhnle, A.; Hofmann, C.; Deininger, P.
2021. CIRP Annals, 70 (1), 381–384. doi:10.1016/j.cirp.2021.04.036

Autonomeous production control for matrix production based on deep Q-learning
Hofmann, C.; Krahe, C.; Stricker, N.; Lanza, G.
2020. Procedia CIRP, 88, 25–30. doi:10.1016/j.procir.2020.05.005

A Data-Driven Approach for Quality Analytics of Screwing Processes in a Global Learning Factory
Yang, S.; Liu, H.; Zhang, Y.; Arndt, T.; Hofmann, C.; Häfner, B.; Lanza, G.
2020. Procedia manufacturing, 45, 454–459. doi:10.1016/j.promfg.2020.04.052

Machine learning based activity recognition to identify wasteful activities in production
Hofmann, C.; Patschkowski, C.; Häfner, B.; Lanza, G.
2020. Procedia manufacturing, 45, 171–176. doi:10.1016/j.promfg.2020.04.090

Augmented Go & See: An approach for improved bottleneck identification in production lines
Hofmann, C.; Staehr, T.; Cohen, S.; Stricker, N.; Haefner, B.; Lanza, G.
2019. 9th Conference on Learning Factories, CLF 2019; Braunschweig; Germany; 26 March 2019 through 28 March 2019. Ed.: C. Herrmann, 148–154, Elsevier. doi:10.1016/j.promfg.2019.03.023

Development of an agile development method based on Kanban for distributed part-time teams and an introduction framework
Hofmann, C.; Lauber, S.; Haefner, B.; Lanza, G.
2018. (D. Mourtzis & G. Chryssolouris, Eds.) Advanced Engineering Education & Training for Manufacturing Innovation Hrsg.: Mourtzis, Dimitris; Chryssolouris, George, 23, 45–50. doi:10.1016/j.promfg.2018.03.159

The Impact of Routing and Operation Flexibility on the Performance of Matrix Production Compared to a Production Line
Hofmann, C.; Brakemeier, N.; Krahe, C.; Stricker, N.; Lanza, G.
2018. R. Schmitt & G. Schuh (Eds.), Advances in Production Research Hrsg.: Schmitt, Robert; Schuh, Günther, 155–165, Springer International Publishing. doi:10.1007/978-3-030-03451-1_16

Auf dem Weg zum Digitalen Shopfloor Management: Eine Studie zum Stand der Echtzeitentscheidungsfähigkeit und des Industrie 4.0-Reifegrads
Lanza, G.; Hofmann, C.; Stricker, N.; Biehl, E.; Braun, Y.
2018. Karlsruher Institut für Technologie (KIT)