---
_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'
...
---
_id: '13460'
abstract:
- lang: eng
  text: 'Remaining useful lifetime (RUL) predictions as part of a condition monitoring
    system are focused in more and more research and industrial applications. To establish
    an efficient and precise estimate of the RUL of a technical product, different  uncertainties  have  to  be  handled.  To  minimize  the  uncertainties  of  the  RUL  estimation,  a  reliable
    and accurate prognostic approach as well as a good failure threshold are important.
    Regarding the failure threshold, most often  an  expert  sets  a  fixed  failure  threshold.  However,  neither  the  a  priori  known  failure  threshold  nor  a  fixedthreshold
    value are feasible in every application. Especially in the case of varying characteristics
    of the monitored system, an adaptive failure threshold is of great importance
    concerning the accuracy of the RUL estimation.  Rubber-metal-elements, which are
    used in a wide range of applications for vibration and sound isolation, are mon-itored
    by thermocouples to allow for lifetime predictions. Therefore, the element’s state
    is described by its temper-ature during its service life. Aiming to establish
    accurate RUL predictions of a rubber-metal-element, uncertainties due to nonlinear
    material characteristics and changing operational conditions have to be considered.
    Consequently, different temperature-based failure threshold definitions are implemented
    and compared within a particle filtering approach. '
author:
- first_name: Amelie
  full_name: Bender, Amelie
  id: '54290'
  last_name: Bender
- first_name: Lennart
  full_name: Schinke, Lennart
  last_name: Schinke
- first_name: Walter
  full_name: Sextro, Walter
  id: '21220'
  last_name: Sextro
citation:
  ama: 'Bender A, Schinke L, Sextro W. Remaining useful lifetime prediction based
    on adaptive failure thresholds. In: Beer M, Zio E, eds. <i>Proceedings of the
    29th European Safety and Reliability Conference (ESREL2019)</i>. ; 2019:1262-1269.'
  apa: Bender, A., Schinke, L., &#38; Sextro, W. (2019). Remaining useful lifetime
    prediction based on adaptive failure thresholds. In M. Beer &#38; E. Zio (Eds.),
    <i>Proceedings of the 29th European Safety and Reliability Conference (ESREL2019)</i>
    (Issue 29, pp. 1262–1269).
  bibtex: '@inproceedings{Bender_Schinke_Sextro_2019, title={Remaining useful lifetime
    prediction based on adaptive failure thresholds}, number={29}, booktitle={Proceedings
    of the 29th European Safety and Reliability Conference (ESREL2019)}, author={Bender,
    Amelie and Schinke, Lennart and Sextro, Walter}, editor={Beer, Michael and Zio,
    Enrico}, year={2019}, pages={1262–1269} }'
  chicago: Bender, Amelie, Lennart Schinke, and Walter Sextro. “Remaining Useful Lifetime
    Prediction Based on Adaptive Failure Thresholds.” In <i>Proceedings of the 29th
    European Safety and Reliability Conference (ESREL2019)</i>, edited by Michael
    Beer and Enrico Zio, 1262–69, 2019.
  ieee: A. Bender, L. Schinke, and W. Sextro, “Remaining useful lifetime prediction
    based on adaptive failure thresholds,” in <i>Proceedings of the 29th European
    Safety and Reliability Conference (ESREL2019)</i>, Hannover, 2019, no. 29, pp.
    1262–1269.
  mla: Bender, Amelie, et al. “Remaining Useful Lifetime Prediction Based on Adaptive
    Failure Thresholds.” <i>Proceedings of the 29th European Safety and Reliability
    Conference (ESREL2019)</i>, edited by Michael Beer and Enrico Zio, no. 29, 2019,
    pp. 1262–69.
  short: 'A. Bender, L. Schinke, W. Sextro, in: M. Beer, E. Zio (Eds.), Proceedings
    of the 29th European Safety and Reliability Conference (ESREL2019), 2019, pp.
    1262–1269.'
conference:
  end_date: 2019.09.26
  location: Hannover
  name: '29th European Safety and Reliability Conference '
  start_date: 2019.09.22
date_created: 2019-09-30T08:49:19Z
date_updated: 2023-09-22T07:31:53Z
department:
- _id: '151'
editor:
- first_name: Michael
  full_name: Beer, Michael
  last_name: Beer
- first_name: Enrico
  full_name: Zio, Enrico
  last_name: Zio
issue: '29'
keyword:
- RUL prediction
- adaptive threshold
- prognostics
- condition monitoring
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: http://rpsonline.com.sg/proceedings/9789811127243/html/0445.xml
oa: '1'
page: 1262-1269
publication: Proceedings of the 29th European Safety and Reliability Conference (ESREL2019)
publication_identifier:
  isbn:
  - 978-981-11-2724-3
publication_status: published
quality_controlled: '1'
status: public
title: Remaining useful lifetime prediction based on adaptive failure thresholds
type: conference
user_id: '54290'
year: '2019'
...