| Solving the Job-Shop Scheduling Problem in the Industry 4.0 Era M Leusin, E Frazzon, M Uriona Maldonado, M Kück, M Freitag Technologies 6 (4), 107, 2018 | 114 | 2018 |
| Data-driven production control for complex and dynamic manufacturing systems EM Frazzon, M Kück, M Freitag CIRP Annals 67 (1), 515-518, 2018 | 111 | 2018 |
| Hybrid approach for the integrated scheduling of production and transport processes along supply chains EM Frazzon, A Albrecht, M Pires, E Israel, M Kück, M Freitag International Journal of Production Research 56 (5), 2019-2035, 2018 | 97 | 2018 |
| Forecasting of customer demands for production planning by local k-nearest neighbor models M Kück, M Freitag International Journal of Production Economics 231, 107837, 2021 | 83 | 2021 |
| Potential of data-driven simulation-based optimization for adaptive scheduling and control of dynamic manufacturing systems M Kück, J Ehm, T Hildebrandt, M Freitag, EM Frazzon 2016 Winter Simulation Conference (WSC), 2820-2831, 2016 | 60 | 2016 |
| Potential of a Multi-Agent System Approach for Production Control in Smart Factories ME Leusin, M Kück, EM Frazzon, MU Maldonado, M Freitag IFAC-PapersOnLine 51 (11), 1459-1464, 2018 | 59 | 2018 |
| Meta-learning with neural networks and landmarking for forecasting model selection an empirical evaluation of different feature sets applied to industry data M Kück, SF Crone, M Freitag 2016 international joint conference on neural networks (IJCNN), 1499-1506, 2016 | 49 | 2016 |
| Prediction of customer demands for production planning–Automated selection and configuration of suitable prediction methods B Scholz-Reiter, M Kück, D Lappe CIRP Annals-Manufacturing Technology 63 (1), 417-420, 2014 | 34 | 2014 |
| Evaluating the Robustness of Production Schedules using Discrete-Event Simulation GE Vieira, M Kück, E Frazzon, M Freitag IFAC-PapersOnLine 50 (1), 7953-7958, 2017 | 32 | 2017 |
| A Data-Driven Simulation-Based Optimisation Approach for Adaptive Scheduling and Control of Dynamic Manufacturing Systems M Kück, J Ehm, M Freitag, EM Frazzon, R Pimentel Advanced Materials Research 1140, 449-456, 2016 | 32 | 2016 |
| Towards adaptive simulation-based optimization to select individual dispatching rules for production control M Kück, E Broda, M Freitag, T Hildebrandt, EM Frazzon Winter Simulation Conference (WSC), 2017, 3852-3863, 2017 | 30 | 2017 |
| Potenziale von Data Science in Produktion und Logistik: Teil 2 - Vorgehensweise zur Datenanalyse und Anwendungsbeispiele M Freitag, M Kück, A Ait Alla, M Lütjen Industrie 4.0 Management 31 (6), 39-46, 2015 | 28* | 2015 |
| Potenziale von Data Science in Produktion und Logistik: Teil 1 - Eine Einführung in aktuelle Ansätze der Data Science M Freitag, M Kück, A Ait Alla, M Lütjen Industrie 4.0 Management 31 (5), 22-26, 2015 | 24* | 2015 |
| Towards a simulation-based optimization approach to integrate supply chain planning and control MC Pires, EM Frazzon, AMC Danielli, M Kück, M Freitag Procedia CIRP 72, 520-525, 2018 | 22 | 2018 |
| Towards Networking Logistics Resources to enable a Demand-Driven Material Supply for Lean Production Systems–Basic Concept and Potential of a Cyber-Physical Logistics System KD Thoben, M Veigt, D Lappe, M Franke, M Kück, R Zimmerling, J Schlick, ... Proceedings of the 7. BVL Scientific Symposium on Logistics, BVL Int …, 2014 | 19 | 2014 |
| A genetic algorithm to optimize lazy learning parameters for the prediction of customer demands M Kück, B Scholz-Reiter Machine Learning and Applications (ICMLA), 2013 12th International …, 2013 | 15 | 2013 |
| Potentials and Risks of Resource Sharing in Production and Logistics M Freitag, M Kück, T Becker Proceedings of the 8th International Scientific Symposium on Logistics, 199-209, 2016 | 11* | 2016 |
| Emergence of Non-predictable Dynamics Caused by Shared Resources in Production Networks M Kück, T Becker, M Freitag Procedia CIRP 41, 520-525, 2016 | 9 | 2016 |
| Using Industry 4.0’s Big Data and IoT to Perform Feature-Based and Past Data-Based Energy Consumption Predictions J Gumz, DC Fettermann, EM Frazzon, M Kück Sustainability 14 (20), 13642, 2022 | 5 | 2022 |
| Robust Methods for the Prediction of Customer Demands based on Nonlinear Dynamical Systems M Kück, B Scholz-Reiter, M Freitag Procedia CIRP 19, 93-98, 2014 | 4 | 2014 |
Michael FreitagProfessor of Production Systems and Logistics, University of Bremen, GermanyBestätigte E-Mail-Adresse bei uni-bremen.de
