---
_id: '63193'
abstract:
- lang: eng
  text: The integration of data-driven models and specifically machine learning for
    conditon monitoring and predictive maintenance into companies, especially small
    and medium-sized enterprises, offers significant opportunities in reducing costs,
    operating more sustainably, and maintaining long-term competitiveness. However,
    many small and medium-sized enterprises lack the necessary resources and expertise
    to derive knowledge from data and integrate their own machine learning based solutions.
    To address this challenge, a framework is presented that enables the automated
    generation of data-driven models with a particular focus on condition monitoring
    and predictive maintenance, but applicable to other use cases as well. Using a
    dataset from the 2022 data challenge of the prognostics and health management
    society, it is demonstrated that the framework can generate high-performing models,
    achieving F1-scores up to 0.998, exemplarily for a classification task.
author:
- first_name: Alexander
  full_name: Löwen, Alexander
  id: '47233'
  last_name: Löwen
- first_name: Dennis
  full_name: Quirin, Dennis
  last_name: Quirin
- first_name: Marc
  full_name: Hesse, Marc
  last_name: Hesse
- first_name: Osarenren Kennedy
  full_name: Aimiyekagbon, Osarenren Kennedy
  id: '9557'
  last_name: Aimiyekagbon
- first_name: Walter
  full_name: Sextro, Walter
  id: '21220'
  last_name: Sextro
citation:
  ama: 'Löwen A, Quirin D, Hesse M, Aimiyekagbon OK, Sextro W. Facilitating the Automated
    Generation of Data-Driven Models for the Diagnostics and Prognostics of Technical
    Systems. In: <i>2025 IEEE 30th International Conference on Emerging Technologies
    and Factory Automation (ETFA)</i>. IEEE; 2025. doi:<a href="https://doi.org/10.1109/etfa65518.2025.11205799">10.1109/etfa65518.2025.11205799</a>'
  apa: Löwen, A., Quirin, D., Hesse, M., Aimiyekagbon, O. K., &#38; Sextro, W. (2025).
    Facilitating the Automated Generation of Data-Driven Models for the Diagnostics
    and Prognostics of Technical Systems. <i>2025 IEEE 30th International Conference
    on Emerging Technologies and Factory Automation (ETFA)</i>. 2025 IEEE 30th International
    Conference on Emerging Technologies and Factory Automation (ETFA), Porto. <a href="https://doi.org/10.1109/etfa65518.2025.11205799">https://doi.org/10.1109/etfa65518.2025.11205799</a>
  bibtex: '@inproceedings{Löwen_Quirin_Hesse_Aimiyekagbon_Sextro_2025, title={Facilitating
    the Automated Generation of Data-Driven Models for the Diagnostics and Prognostics
    of Technical Systems}, DOI={<a href="https://doi.org/10.1109/etfa65518.2025.11205799">10.1109/etfa65518.2025.11205799</a>},
    booktitle={2025 IEEE 30th International Conference on Emerging Technologies and
    Factory Automation (ETFA)}, publisher={IEEE}, author={Löwen, Alexander and Quirin,
    Dennis and Hesse, Marc and Aimiyekagbon, Osarenren Kennedy and Sextro, Walter},
    year={2025} }'
  chicago: Löwen, Alexander, Dennis Quirin, Marc Hesse, Osarenren Kennedy Aimiyekagbon,
    and Walter Sextro. “Facilitating the Automated Generation of Data-Driven Models
    for the Diagnostics and Prognostics of Technical Systems.” In <i>2025 IEEE 30th
    International Conference on Emerging Technologies and Factory Automation (ETFA)</i>.
    IEEE, 2025. <a href="https://doi.org/10.1109/etfa65518.2025.11205799">https://doi.org/10.1109/etfa65518.2025.11205799</a>.
  ieee: 'A. Löwen, D. Quirin, M. Hesse, O. K. Aimiyekagbon, and W. Sextro, “Facilitating
    the Automated Generation of Data-Driven Models for the Diagnostics and Prognostics
    of Technical Systems,” presented at the 2025 IEEE 30th International Conference
    on Emerging Technologies and Factory Automation (ETFA), Porto, 2025, doi: <a href="https://doi.org/10.1109/etfa65518.2025.11205799">10.1109/etfa65518.2025.11205799</a>.'
  mla: Löwen, Alexander, et al. “Facilitating the Automated Generation of Data-Driven
    Models for the Diagnostics and Prognostics of Technical Systems.” <i>2025 IEEE
    30th International Conference on Emerging Technologies and Factory Automation
    (ETFA)</i>, IEEE, 2025, doi:<a href="https://doi.org/10.1109/etfa65518.2025.11205799">10.1109/etfa65518.2025.11205799</a>.
  short: 'A. Löwen, D. Quirin, M. Hesse, O.K. Aimiyekagbon, W. Sextro, in: 2025 IEEE
    30th International Conference on Emerging Technologies and Factory Automation
    (ETFA), IEEE, 2025.'
conference:
  location: Porto
  name: 2025 IEEE 30th International Conference on Emerging Technologies and Factory
    Automation (ETFA)
date_created: 2025-12-18T09:07:38Z
date_updated: 2025-12-18T09:12:48Z
department:
- _id: '151'
doi: 10.1109/etfa65518.2025.11205799
language:
- iso: eng
project:
- _id: '1483'
  name: Industrie 4.0 Ökosystem für den automatisierten Einsatz von datengetriebenen
    Services (I4.0AutoServ)
publication: 2025 IEEE 30th International Conference on Emerging Technologies and
  Factory Automation (ETFA)
publication_status: published
publisher: IEEE
related_material:
  link:
  - relation: confirmation
    url: https://ieeexplore.ieee.org/document/11205799
status: public
title: Facilitating the Automated Generation of Data-Driven Models for the Diagnostics
  and Prognostics of Technical Systems
type: conference
user_id: '47233'
year: '2025'
...