---
_id: '55336'
abstract:
- lang: eng
  text: "Predicting the remaining useful life of technical \r\nsystems has gained
    significant attention in recent years due to \r\nincreasing demands for extending
    the lifespan of degrading system \r\ncomponents. Therefore, already used systems
    are retrofitted by \r\nintegrating sensors to monitor their performance and \r\nfunctionality,
    enabling accurate diagnosis of their condition and \r\nprediction of their remaining
    useful life. One of the main \r\nchallenges in this field is identified in the
    missing data from the \r\ntime where the retrofitted system has already run but
    without \r\nbeing monitored by sensors. In this paper, a novel approach for \r\nthe
    combined diagnostics and prognostics of retrofitted systems is \r\nproposed. The
    methodology aims to provide an accurate diagnosis \r\nof the system’s health state
    and estimation of the remaining useful \r\nlife by a combination of a machine
    learning and expert knowledge. \r\nTo evaluate the effectiveness of the proposed
    methodology, a case \r\nstudy involving a retrofitted system in an industrial
    setting is \r\nselected and applied. It is demonstrated that the approach \r\neffectively
    diagnose the current system’s health state and \r\naccurately predict its remaining
    useful life, thereby enabling \r\npredictive maintenance and decision-making.
    Overall, our \r\nresearch contributes to advancing the field of condition \r\nmonitoring
    for retrofitted systems by providing a comprehensive \r\nmethodology that addresses
    the challenge of missing data."
author:
- first_name: Amelie
  full_name: Bender, Amelie
  id: '54290'
  last_name: Bender
- 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: 'Bender A, Aimiyekagbon OK, Sextro W. Diagnostics and Prognostics for Retrofitted
    Systems: A Comprehensive Approach for Enhanced System Health Assessment. In: <i>Proceedings
    of the 2024 Prognostics and System Health Management Conference (PHM)</i>. IEEE
    Computer Society; 2024. doi:<a href="https://doi.org/10.1109/PHM61473.2024.00038">10.1109/PHM61473.2024.00038</a>'
  apa: 'Bender, A., Aimiyekagbon, O. K., &#38; Sextro, W. (2024). Diagnostics and
    Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System
    Health Assessment. <i>Proceedings of the 2024 Prognostics and System Health Management
    Conference (PHM)</i>. 2024 Prognostics and System Health Management Conference
    (PHM), Stockholm, Schweden. <a href="https://doi.org/10.1109/PHM61473.2024.00038">https://doi.org/10.1109/PHM61473.2024.00038</a>'
  bibtex: '@inproceedings{Bender_Aimiyekagbon_Sextro_2024, title={Diagnostics and
    Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System
    Health Assessment}, DOI={<a href="https://doi.org/10.1109/PHM61473.2024.00038">10.1109/PHM61473.2024.00038</a>},
    booktitle={Proceedings of the 2024 Prognostics and System Health Management Conference
    (PHM)}, publisher={IEEE Computer Society}, author={Bender, Amelie and Aimiyekagbon,
    Osarenren Kennedy and Sextro, Walter}, year={2024} }'
  chicago: 'Bender, Amelie, Osarenren Kennedy Aimiyekagbon, and Walter Sextro. “Diagnostics
    and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced
    System Health Assessment.” In <i>Proceedings of the 2024 Prognostics and System
    Health Management Conference (PHM)</i>. IEEE Computer Society, 2024. <a href="https://doi.org/10.1109/PHM61473.2024.00038">https://doi.org/10.1109/PHM61473.2024.00038</a>.'
  ieee: 'A. Bender, O. K. Aimiyekagbon, and W. Sextro, “Diagnostics and Prognostics
    for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment,”
    presented at the 2024 Prognostics and System Health Management Conference (PHM),
    Stockholm, Schweden, 2024, doi: <a href="https://doi.org/10.1109/PHM61473.2024.00038">10.1109/PHM61473.2024.00038</a>.'
  mla: 'Bender, Amelie, et al. “Diagnostics and Prognostics for Retrofitted Systems:
    A Comprehensive Approach for Enhanced System Health Assessment.” <i>Proceedings
    of the 2024 Prognostics and System Health Management Conference (PHM)</i>, IEEE
    Computer Society, 2024, doi:<a href="https://doi.org/10.1109/PHM61473.2024.00038">10.1109/PHM61473.2024.00038</a>.'
  short: 'A. Bender, O.K. Aimiyekagbon, W. Sextro, in: Proceedings of the 2024 Prognostics
    and System Health Management Conference (PHM), IEEE Computer Society, 2024.'
conference:
  end_date: 2024-05-31
  location: Stockholm, Schweden
  name: 2024 Prognostics and System Health Management Conference (PHM)
  start_date: 2024-05-28
date_created: 2024-07-22T09:27:57Z
date_updated: 2024-07-22T09:29:26Z
department:
- _id: '151'
doi: 10.1109/PHM61473.2024.00038
keyword:
- retrofit
- diagnosis
- prognostics
- RUL prediction
- missing data
- ball bearings
language:
- iso: eng
publication: Proceedings of the 2024 Prognostics and System Health Management Conference
  (PHM)
publication_identifier:
  isbn:
  - 979-8-3503-6058-5
publisher: IEEE Computer Society
quality_controlled: '1'
status: public
title: 'Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach
  for Enhanced System Health Assessment'
type: conference
user_id: '54290'
year: '2024'
...