| A survey on predictive maintenance for industry 4.0 C Krupitzer, T Wagenhals, M Züfle, V Lesch, D Schäfer, A Mozaffarin, ... arXiv preprint arXiv:2002.08224, 2020 | 54 | 2020 |
| A survey on human machine interaction in industry 4.0 C Krupitzer, S Müller, V Lesch, M Züfle, J Edinger, A Lemken, D Schäfer, ... arXiv preprint arXiv:2002.01025, 2020 | 49 | 2020 |
| A machine learning-based workflow for automatic detection of anomalies in machine tools M Züfle, F Moog, V Lesch, C Krupitzer, S Kounev ISA transactions 125, 445-458, 2022 | 31 | 2022 |
| Time series forecasting for self-aware systems A Bauer, M Züfle, N Herbst, A Zehe, A Hotho, S Kounev Proceedings of the IEEE 108 (7), 1068-1093, 2020 | 31 | 2020 |
| Autonomic forecasting method selection: Examination and ways ahead M Züfle, A Bauer, V Lesch, C Krupitzer, N Herbst, S Kounev, V Curtef 2019 IEEE International conference on autonomic computing (ICAC), 167-176, 2019 | 30 | 2019 |
| A literature review of IoT and CPS—What they are, and what they are not V Lesch, M Züfle, A Bauer, L Iffländer, C Krupitzer, S Kounev Journal of Systems and Software 200, 111631, 2023 | 26 | 2023 |
| Telescope: An automatic feature extraction and transformation approach for time series forecasting on a level-playing field A Bauer, M Züfle, N Herbst, S Kounev, V Curtef 2020 IEEE 36th International Conference on Data Engineering (ICDE), 1902-1905, 2020 | 21 | 2020 |
| An automated forecasting framework based on method recommendation for seasonal time series A Bauer, M Züfle, J Grohmann, N Schmitt, N Herbst, S Kounev Proceedings of the ACM/SPEC International Conference on Performance …, 2020 | 21 | 2020 |
| Libra: A benchmark for time series forecasting methods A Bauer, M Züfle, S Eismann, J Grohmann, N Herbst, S Kounev Proceedings of the ACM/SPEC International Conference on Performance …, 2021 | 19 | 2021 |
| Telescope: a hybrid forecast method for univariate time series M Züfle, A Bauer, N Herbst, V Curtef, S Kounev International work-conference on Time Series (ITISE 2017), 2017 | 19 | 2017 |
| A predictive maintenance methodology: predicting the time-to-failure of machines in industry 4.0 M Züfle, J Agne, J Grohmann, I Dörtoluk, S Kounev 2021 IEEE 19th International Conference on Industrial Informatics (INDIN), 1-8, 2021 | 14 | 2021 |
| To fail or not to fail: Predicting hard disk drive failure time windows M Züfle, C Krupitzer, F Erhard, J Grohmann, S Kounev Measurement, Modelling and Evaluation of Computing Systems: 20th …, 2020 | 13 | 2020 |
| A survey on predictive maintenance for industry 4.0. arXiv 2020 C Krupitzer, T Wagenhals, M Züfle, V Lesch, D Schäfer, A Mozaffarin, ... arXiv preprint arXiv:2002.08224, 0 | 10 | |
| A Survey on Human Machine Interaction in Industry 4.0. arXiv 2020 C Krupitzer, S Müller, V Lesch, M Züfle, J Edinger, A Lemken, D Schäfer, ... arXiv preprint arXiv:2002.01025, 0 | 8 | |
| Utilizing clustering to optimize resource demand estimation approaches J Grohmann, S Eismann, A Bauer, M Zuefle, N Herbst, S Kounev 2019 IEEE 4th International Workshops on Foundations and Applications of …, 2019 | 6 | 2019 |
| Machine learning model update strategies for hard disk drive failure prediction M Züfle, F Erhard, S Kounev 2021 20th IEEE International conference on machine learning and applications …, 2021 | 5 | 2021 |
| A framework for time series preprocessing and history-based forecasting method recommendation M Züfle, S Kounev 2020 15th Conference on Computer Science and Information Systems (FedCSIS …, 2020 | 5 | 2020 |
| Recommendations for data-driven degradation estimation with case studies from manufacturing and dry-bulk shipping N Finke, M Mohr, A Lontke, M Züfle, S Kounev, R Möller International Conference on Research Challenges in Information Science, 189-204, 2021 | 3 | 2021 |
| Best practices for time series forecasting (tutorial) A Bauer, M Züfle, N Herbst, S Kounev 2019 IEEE 4th International Workshops on Foundations and Applications of …, 2019 | 3 | 2019 |
| Dynamic Hybrid Forecasting for Self-Aware Systems M Züfle Master Thesis. Würzburg, Germany: Department of Computer Science …, 2017 | 3 | 2017 |
