3D modeling from a single image via a novel dual-decoder framework for Agile design
Peng, J.; Kimmig, A.; Kreuzwieser, S.; Niu, Z.; Tao, X.; Ovtcharova, J.
2025. Computers in Industry, 169, 104303. doi:10.1016/j.compind.2025.104303

Hesse-Matrix-basierte Qualitätsmanagementsysteme für die Fertigungsindustrie
Jieyang, P.; Dongkun, W.; Kimmig, A.; Zhang, B.; Roux, A.; Ovtcharova, J.
2025. at - Automatisierungstechnik, 73 (1), 61–80. doi:10.1515/auto-2024-0004

A systematic review of current AI techniques used in the context of the SDGs
Greif, L.; Röckel, F.; Kimmig, A.; Ovtcharova, J.
2025. International Journal of Environmental Research, 19 (1), Art.-Nr.: 1. doi:10.1007/s41742-024-00668-5

A Knowledge Graph Framework to Support Life Cycle Assessment for Sustainable Decision-Making
Greif, L.; Hauck, S.; Kimmig, A.; Ovtcharova, J.
2025. Applied Sciences, 15 (1), 175. doi:10.3390/app15010175

Meta-learning enhanced adaptive robot control strategy for automated PCB assembly
Peng, J.; Wang, D.; Zhao, J.; Teng, Y.; Kimmig, A.; Tao, X.; Ovtcharova, J.
2025. Journal of Manufacturing Systems, 78, 46 – 57. doi:10.1016/j.jmsy.2024.11.009

Carbon footprint tracing and pattern recognition framework based on visual analytics
Peng, J.; Kimmig, A.; Wang, D.; Niu, Z.; Liu, X.; Tao, X.; Ovtcharova, J.
2024. Sustainable Production and Consumption, 50, 327–346. doi:10.1016/j.spc.2024.07.019

Energy consumption forecasting based on spatio-temporal behavioral analysis for demand-side management
Peng, J.; Kimmig, A.; Wang, D.; Niu, Z.; Liu, X.; Tao, X.; Ovtcharova, J.
2024. Applied Energy, 374, 124027. doi:10.1016/j.apenergy.2024.124027

Strategic view on the current role of AI in advancing environmental sustainability: a SWOT analysis
Greif, L.; Kimmig, A.; El Bobbou, S.; Jurisch, P.; Ovtcharova, J.
2024. Discover Artificial Intelligence, 4 (1), Art.-Nr.: 45. doi:10.1007/s44163-024-00146-z

Product quality recognition and its industrial application based on lightweight machine learning
Peng, J.; Wang, D.; Kreuzwieser, S.; Kimmig, A.; Tao, X.; Wang, L.; Ovtcharova, J.
2024. Engineering Optimization, 56 (12), 2242–2267. doi:10.1080/0305215X.2024.2305242

Intention recognition-based human–machine interaction for mixed flow assembly
Peng, J.; Kimmig, A.; Wang, D.; Niu, Z.; Tao, X.; Ovtcharova, J.
2024. Journal of Manufacturing Systems, 72, 229 – 244. doi:10.1016/j.jmsy.2023.11.021

Human-Machine-Interaction in Innovative Work Environment 4.0 – A Human-Centered Approach
Kreuzwieser, S.; Kimmig, A.; Michels, F.; Bulander, R.; Häfner, V.; Bönsch, J.; Ovtcharova, J.
2023. New Digital Work – Digital Sovereignty at the Workplace. Ed.: A. Shajek, 68–86, Springer International Publishing. doi:10.1007/978-3-031-26490-0_ 5

A systematic review of data-driven approaches to fault diagnosis and early warning
Jieyang, P.; Kimmig, A.; Dongkun, W.; Niu, Z.; Zhi, F.; Jiahai, W.; Jiahai, W.; Liu, X.
2022. Journal of Intelligent Manufacturing, 34 (8), 3277–3304. doi:10.1007/s10845-022-02020-0

A subject-oriented reference model for Digital Twins
Bönsch, J.; Elstermann, M.; Kimmig, A.; Ovtcharova, J.
2022. Computers and Industrial Engineering, 172 (Part A), Art.-Nr.: 108556. doi:10.1016/j.cie.2022.108556

Concept for the Configuration of Turnkey Production Systems
Gönnheimer, P.; Kimmig, A.; Ehrmann, C.; Schlechtendahl, J.; Güth, J.; Fleischer, J.
2019. (F. Dietrich & N. Krenkel, Hrsg.) Procedia CIRP Hrsg.: Dietrich, Franz; Krenkel, Nicole, 86, 234–238. doi:10.1016/j.procir.2020.01.047

Final Report Sino-German Industry 4.0 Factory Automation Platform
Albers, A.; Ovtcharova, J.; Becker, J.; Lanza, G.; Zhang, W.; Zhang, T.; Qiao, F.; Ma, Y.; Wang, J.; Wu, Z.; Ehrmann, C.; Gönnheimer, P.; Behrendt, M.; Mandel, C.; Stürmlinger, T.; Klippert, M.; Kimmig, A.; Schade, F.; Yang, S.; Heider, I.; Xie, S.; Song, K.; Peng, J.; Goncalves, P.; Kampfmann, R.; Schlechtendahl, J.; Kattner, J.; Straub, C.; May, M.; Zhu, Z.; Bai, O.; Lin, Y.; Yang, Z.; Ding, L.; Rossol, A.-S.
2022. (J. Fleischer, Hrsg.), Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000143693

Wertstromkinematik – Produktionssysteme neu gedacht: Interdisziplinäres Forscherteam arbeitet an der Produktionstechnik der Zukunft (Teil 2)
Kimmig, A.; Schöck, M.; Mühlbeier, E.; Oexle, F.; Fleischer, J.; Bönsch, J.; Ovtcharova, J.; Hahn, J.; Grunwald, A.; Albers, A.; Rapp, S.; Hagenmeyer, V.; Scholz, S. G.; Schmidt, A.; Müller, T.; Becker, J.; Schade, F.; Beyerer, J.; Rehak, J.; Zwick, T.; Pauli, M.; Nuß, B.; Lanza, G.; Schild, L.; Overbeck, L.
2021. Zeitschrift für wirtschaftlichen Fabrikbetrieb, 116 (12), 935–939. doi:10.1515/zwf-2021-0207

Konzeption und Entwicklung eines Produktionsanlagenkonfigurators : Im Rahmen einer deutsch-chinesischen Industrie-4.0-Fabrikautomatisierungsplattform = Conception and Development of a Production System Configurator
Gönnheimer, P.; Ehrmann, C.; Wu, Y.; Kimmig, A.; Fleischer, J.
2021. ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb, 116 (11), 836–840. doi:10.1515/zwf-2021-0193

Wind turbine failure prediction and health assessment based on adaptive maximum mean discrepancy
Peng, J.; Kimmig, A.; Niu, Z.; Wang, J.; Liu, X.; Wang, D.; Ovtcharova, J.
2022. International journal of electrical power & energy systems, 134, Art.Nr. 107391. doi:10.1016/j.ijepes.2021.107391

Dual-stage attention-based long-short-term memory neural networks for energy demand prediction
Peng, J.; Kimmig, A.; Wang, J.; Liu, X.; Niu, Z.; Ovtcharova, J.
2021. Energy and buildings, 249, Art.-Nr.: 111211. doi:10.1016/j.enbuild.2021.111211

Human-Centered Referential Process Models for AI Application
Elstermann, M.; Bönsch, J.; Kimmig, A.; Ovtcharova, J.
2021. Human Centred Intelligent Systems: Proceedings of KES-HCIS 2021 Conference. Ed.: A. Zimmermann, 56–65, Springer. doi:10.1007/978-981-16-3264-8_6

A flexible potential-flow model based high resolution spatiotemporal energy demand forecasting framework
Peng, J.; Kimmig, A.; Niu, Z.; Wang, J.; Liu, X.; Ovtcharova, J.
2021. Applied Energy, 299, Art.-Nr.: 117321. doi:10.1016/j.apenergy.2021.117321

Ein hybrides RNN-Modell für die mittel- bis langfristige Vorhersage des Strombedarfs unter Berücksichtigung von Wettereinflüssen [A hybrid RNN model for mid-to-long term electricity demand forecasting incorporating weather influences]
Jieyang, P.; Dongkun, W.; Kimmig, A.; Langovoy, M. A.; Jiahai, W.; Ovtcharova, J.
2021. Automatisierungstechnik, 69 (1), 73–83. doi:10.1515/auto-2020-0033

The Research of Flexible Scheduling of Workshop Based on Artificial Fish Swarm Algorithm and Knowledge Mining
Peng, J.; Wang, J.; Wang, D.; Kimmig, A.; Ovtcharova, J.
2020. Advances in Swarm Intelligence – 11th International Conference, ICSI 2020, Belgrade, Serbia, July 14–20, 2020, Proceedings. Ed.: Y. Tan, 104–116, Springer International Publishing. doi:10.1007/978-3-030-53956-6_10

Methodical approach for the development of a platform for the configuration and operation of turnkey production systems
Gönnheimer, P.; Kimmig, A.; Mandel, C.; Stürmlinger, T.; Yang, S.; Schade, F.; Ehrmann, C.; Klee, B.; Behrendt, M.; Schlechtendahl, J.; Fischer, M.; Trautmann, K.; Fleischer, J.; Lanza, G.; Ovtcharova, J.; Becker, J.; Albers, A.
2019. Procedia CIRP, 84, 880–885. doi:10.1016/j.procir.2019.04.260