Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes
T. Voigt, M. Schöne, M. Kohlhase, O. Nelles, M. Kuhn, in: H. Yin, D. Camacho, P. Tino (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, Springer International Publishing, Cham, 2022, pp. 379–390.
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Konferenzbeitrag
| Veröffentlicht
| Englisch
Autor*in
Herausgeber*in
Yin, Hujun;
Camacho, David;
Tino, Peter
Erscheinungsjahr
Titel des Konferenzbandes
Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings
Seite
379-390
Konferenz
23rd International Conference, IDEAL 2022
Konferenzort
Manchester, UK
Konferenzdatum
2022-11-24 – 2022-11-26
ISBN
ISSN
eISSN
FH-PUB-ID
Zitieren
Voigt, Tim ; Schöne, Marvin ; Kohlhase, Martin ; Nelles, Oliver ; Kuhn, Martin: Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes. In: Yin, H. ; Camacho, D. ; Tino, P. (Hrsg.): Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, Lecture Notes in Computer Science. Cham : Springer International Publishing, 2022, S. 379–390
Voigt T, Schöne M, Kohlhase M, Nelles O, Kuhn M. Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes. In: Yin H, Camacho D, Tino P, eds. Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings. Lecture Notes in Computer Science. Cham: Springer International Publishing; 2022:379-390. doi:10.1007/978-3-031-21753-1_37
Voigt, T., Schöne, M., Kohlhase, M., Nelles, O., & Kuhn, M. (2022). Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes. In H. Yin, D. Camacho, & P. Tino (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings (pp. 379–390). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-21753-1_37
@inproceedings{Voigt_Schöne_Kohlhase_Nelles_Kuhn_2022, place={Cham}, series={Lecture Notes in Computer Science}, title={Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes}, DOI={10.1007/978-3-031-21753-1_37}, booktitle={Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings}, publisher={Springer International Publishing}, author={Voigt, Tim and Schöne, Marvin and Kohlhase, Martin and Nelles, Oliver and Kuhn, Martin}, editor={Yin, Hujun and Camacho, David and Tino, PeterEditors}, year={2022}, pages={379–390}, collection={Lecture Notes in Computer Science} }
Voigt, Tim, Marvin Schöne, Martin Kohlhase, Oliver Nelles, and Martin Kuhn. “Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes.” In Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, edited by Hujun Yin, David Camacho, and Peter Tino, 379–90. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-21753-1_37.
T. Voigt, M. Schöne, M. Kohlhase, O. Nelles, and M. Kuhn, “Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes,” in Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, Manchester, UK, 2022, pp. 379–390.
Voigt, Tim, et al. “Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes.” Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, edited by Hujun Yin et al., Springer International Publishing, 2022, pp. 379–90, doi:10.1007/978-3-031-21753-1_37.