---
_id: '50649'
abstract:
- lang: eng
  text: The energy turnaround and the shift towards sustainable mobility threaten
    the stability of European energy distribution grids due to substantially increasing
    load fluctuations and power demand. These challenges can critically impact assets
    in the distribution grid—e.g., switchgears—intensifying the need to plan, conduct,
    and manage the maintenance of such assets. Predictive maintenance strategies that
    analyze assets' current and historical condition data have been discussed as promising
    approaches toward that end. However, the extant research focuses on designing
    and improving analytical algorithms or information technology (IT) artifacts while
    not considering how a maintenance service is cocreated by companies with IT. This
    research article posits that IT and service must be aligned closely, presenting
    an ensemble artifact comprising a digital industrial platform and a smart service
    system for predictive maintenance on the distribution grid. The artifact is evaluated
    by conducting a willingness-to-pay analysis with asset operators, documenting
    their demand for condition monitoring and predictive maintenance as an integrated
    solution, although they still struggle with even getting the condition data of
    their assets. Building on these results, we formalize the knowledge in the form
    of design principles and implications for managing the maintenance of critical
    assets in the distribution grid.
article_type: original
author:
- first_name: Philipp
  full_name: zur Heiden, Philipp
  id: '64394'
  last_name: zur Heiden
- first_name: Jennifer
  full_name: Priefer, Jennifer
  id: '82872'
  last_name: Priefer
- first_name: Daniel
  full_name: Beverungen, Daniel
  id: '59677'
  last_name: Beverungen
citation:
  ama: zur Heiden P, Priefer J, Beverungen D. Predictive Maintenance on the Energy
    Distribution Grid—Design and Evaluation of a Digital Industrial Platform in the
    Context of a Smart Service System. <i>IEEE Transactions on Engineering Management</i>.
    2024;71:3641-3655. doi:<a href="https://doi.org/10.1109/tem.2024.3352819">10.1109/tem.2024.3352819</a>
  apa: zur Heiden, P., Priefer, J., &#38; Beverungen, D. (2024). Predictive Maintenance
    on the Energy Distribution Grid—Design and Evaluation of a Digital Industrial
    Platform in the Context of a Smart Service System. <i>IEEE Transactions on Engineering
    Management</i>, <i>71</i>, 3641–3655. <a href="https://doi.org/10.1109/tem.2024.3352819">https://doi.org/10.1109/tem.2024.3352819</a>
  bibtex: '@article{zur Heiden_Priefer_Beverungen_2024, title={Predictive Maintenance
    on the Energy Distribution Grid—Design and Evaluation of a Digital Industrial
    Platform in the Context of a Smart Service System}, volume={71}, DOI={<a href="https://doi.org/10.1109/tem.2024.3352819">10.1109/tem.2024.3352819</a>},
    journal={IEEE Transactions on Engineering Management}, publisher={Institute of
    Electrical and Electronics Engineers (IEEE)}, author={zur Heiden, Philipp and
    Priefer, Jennifer and Beverungen, Daniel}, year={2024}, pages={3641–3655} }'
  chicago: 'Heiden, Philipp zur, Jennifer Priefer, and Daniel Beverungen. “Predictive
    Maintenance on the Energy Distribution Grid—Design and Evaluation of a Digital
    Industrial Platform in the Context of a Smart Service System.” <i>IEEE Transactions
    on Engineering Management</i> 71 (2024): 3641–55. <a href="https://doi.org/10.1109/tem.2024.3352819">https://doi.org/10.1109/tem.2024.3352819</a>.'
  ieee: 'P. zur Heiden, J. Priefer, and D. Beverungen, “Predictive Maintenance on
    the Energy Distribution Grid—Design and Evaluation of a Digital Industrial Platform
    in the Context of a Smart Service System,” <i>IEEE Transactions on Engineering
    Management</i>, vol. 71, pp. 3641–3655, 2024, doi: <a href="https://doi.org/10.1109/tem.2024.3352819">10.1109/tem.2024.3352819</a>.'
  mla: zur Heiden, Philipp, et al. “Predictive Maintenance on the Energy Distribution
    Grid—Design and Evaluation of a Digital Industrial Platform in the Context of
    a Smart Service System.” <i>IEEE Transactions on Engineering Management</i>, vol.
    71, Institute of Electrical and Electronics Engineers (IEEE), 2024, pp. 3641–55,
    doi:<a href="https://doi.org/10.1109/tem.2024.3352819">10.1109/tem.2024.3352819</a>.
  short: P. zur Heiden, J. Priefer, D. Beverungen, IEEE Transactions on Engineering
    Management 71 (2024) 3641–3655.
date_created: 2024-01-19T11:47:56Z
date_updated: 2024-11-11T09:50:34Z
ddc:
- '620'
doi: 10.1109/tem.2024.3352819
file:
- access_level: closed
  content_type: application/pdf
  creator: dabe
  date_created: 2024-04-18T12:26:27Z
  date_updated: 2024-04-18T12:26:27Z
  file_id: '53570'
  file_name: Predictive_Maintenance_on_the_Energy_Distribution_GridDesign_and_Evaluation_of_a_Digital_Industrial_Platform_in_the_Context_of_a_Smart_Service_System.pdf
  file_size: 4070804
  relation: main_file
  success: 1
file_date_updated: 2024-04-18T12:26:27Z
has_accepted_license: '1'
intvolume: '        71'
keyword:
- Design science research
- digital platform
- distribution grid
- IS design
- predictive maintenance
- smart services
language:
- iso: eng
page: 3641-3655
project:
- _id: '651'
  grant_number: 03E16012F
  name: 'FLEMING: FLEMING - Flexible Monitoring- und Regelsysteme für die Energie-
    und Mobilitätswende im Verteilnetz durch Einsatz von Künstlicher Intelligenz'
publication: IEEE Transactions on Engineering Management
publication_identifier:
  issn:
  - 0018-9391
  - 1558-0040
publication_status: published
publisher: Institute of Electrical and Electronics Engineers (IEEE)
quality_controlled: '1'
status: public
title: Predictive Maintenance on the Energy Distribution Grid—Design and Evaluation
  of a Digital Industrial Platform in the Context of a Smart Service System
type: journal_article
user_id: '82872'
volume: 71
year: '2024'
...
---
_id: '25046'
abstract:
- lang: eng
  text: <jats:p>While increasing digitalization enables multiple advantages for a
    reliable operation of technical systems, a remaining challenge in the context
    of condition monitoring is seen in suitable consideration of uncertainties affecting
    the monitored system. Therefore, a suitable prognostic approach to predict the
    remaining useful lifetime of complex technical systems is required. To handle
    different kinds of uncertainties, a novel Multi-Model-Particle Filtering-based
    prognostic approach is developed and evaluated by the use case of rubber-metal-elements.
    These elements are maintained preventively due to the strong influence of uncertainties
    on their behavior. In this paper, two measurement quantities are compared concerning
    their ability to establish a prediction of the remaining useful lifetime of the
    monitored elements and the influence of present uncertainties. Based on three
    performance indices, the results are evaluated. A comparison with predictions
    of a classical Particle Filter underlines the superiority of the developed Multi-Model-Particle
    Filter. Finally, the value of the developed method for enabling condition monitoring
    of technical systems related to uncertainties is given exemplary by a comparison
    between the preventive and the predictive maintenance strategy for the use case.</jats:p>
article_number: '210'
article_type: original
author:
- first_name: Amelie
  full_name: Bender, Amelie
  id: '54290'
  last_name: Bender
citation:
  ama: Bender A. A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider
    Uncertainties in RUL Predictions. <i>Machines</i>. 2021;9(10). doi:<a href="https://doi.org/10.3390/machines9100210">10.3390/machines9100210</a>
  apa: Bender, A. (2021). A Multi-Model-Particle Filtering-Based Prognostic Approach
    to Consider Uncertainties in RUL Predictions. <i>Machines</i>, <i>9</i>(10), Article
    210. <a href="https://doi.org/10.3390/machines9100210">https://doi.org/10.3390/machines9100210</a>
  bibtex: '@article{Bender_2021, title={A Multi-Model-Particle Filtering-Based Prognostic
    Approach to Consider Uncertainties in RUL Predictions}, volume={9}, DOI={<a href="https://doi.org/10.3390/machines9100210">10.3390/machines9100210</a>},
    number={10210}, journal={Machines}, author={Bender, Amelie}, year={2021} }'
  chicago: Bender, Amelie. “A Multi-Model-Particle Filtering-Based Prognostic Approach
    to Consider Uncertainties in RUL Predictions.” <i>Machines</i> 9, no. 10 (2021).
    <a href="https://doi.org/10.3390/machines9100210">https://doi.org/10.3390/machines9100210</a>.
  ieee: 'A. Bender, “A Multi-Model-Particle Filtering-Based Prognostic Approach to
    Consider Uncertainties in RUL Predictions,” <i>Machines</i>, vol. 9, no. 10, Art.
    no. 210, 2021, doi: <a href="https://doi.org/10.3390/machines9100210">10.3390/machines9100210</a>.'
  mla: Bender, Amelie. “A Multi-Model-Particle Filtering-Based Prognostic Approach
    to Consider Uncertainties in RUL Predictions.” <i>Machines</i>, vol. 9, no. 10,
    210, 2021, doi:<a href="https://doi.org/10.3390/machines9100210">10.3390/machines9100210</a>.
  short: A. Bender, Machines 9 (2021).
date_created: 2021-09-27T07:07:58Z
date_updated: 2022-11-03T11:42:46Z
department:
- _id: '151'
doi: 10.3390/machines9100210
intvolume: '         9'
issue: '10'
keyword:
- prognostics
- RUL predictions
- particle filter
- uncertainty consideration
- Multi-Model-Particle Filter
- model-based approach
- rubber-metal-elements
- predictive maintenance
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.mdpi.com/2075-1702/9/10/210
oa: '1'
publication: Machines
publication_identifier:
  issn:
  - 2075-1702
publication_status: published
quality_controlled: '1'
status: public
title: A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties
  in RUL Predictions
type: journal_article
user_id: '54290'
volume: 9
year: '2021'
...
---
_id: '21630'
abstract:
- lang: ger
  text: Eine zustandsbasierte Instandhaltungsstrategie reduziert das Risiko eines
    Ausfalls eines technischen Systems bei gleichzeitig hoher Ausnutzung und planbaren
    Instandhaltungsmaßnahmen. Das Ziel dieser Arbeit liegt in der Entwicklung einer
    Zustandsüberwachung für Gummi-Metall-Elemente. Die Herausforderungen dieser Zustandsüberwachung
    leiten sich aus dem viskoelastischen Verhalten sowie dem komplexen Degradationsverhalten
    der Elemente ab. Infolge der daraus resultierenden Unsicherheiten werden die Elemente
    heutzutage präventiv instandgehalten. In Lebensdauerversuchen der Gummi-Metall-Elemente
    werden drei Messgrößen detektiert. Dabei wird mit der Temperatur eine Messgröße
    identifiziert, die am geeignetsten zur Beschreibung des Zustands der Elemente
    ist. Generell wird die Genauigkeit einer Zustandsüberwachung durch verschiedene
    Unsicherheiten beeinflusst. Für die Prognose der nutzbaren Restlebensdauer der
    Gummi-Metall-Elemente wird das Partikelfilter, eine verbreitete modellbasierte
    Methode zur Zustandsüberwachung technischer Systeme, weiterentwickelt, um Unsicherheiten
    im Verhalten und der Degradation der Elemente zu berücksichtigen. Anhand der Ergebnisse
    wird belegt, dass aufbauend auf dieser Zustandsüberwachung die Ausnutzung der
    Gummi-Metall-Elemente in realen Anwendungen durch eine präventive Instandhaltung
    erhöht werden kann. Damit bildet diese Arbeit die Basis für zukünftige, prädiktive
    Instandhaltungskonzepte für diese Elemente. Weiterhin bestätigt die Arbeit, dass
    eine Berücksichtigung vorliegender Unsicherheiten zu einem frühen Zeitpunkt im
    Entwicklungsprozess des Zustandsüberwachungssystems empfehlenswert ist.
- lang: eng
  text: With condition-based maintenance, the risk of system failure is reduced while
    maximizing system utilization and ensuring a predictable maintenance schedule.
    The aim of this thesis is the development of a condition monitoring system of
    rubber-metal-elements. Due to the viscoelasticity and the complex degradation
    behavior of the elements, they are currently maintained preventively. During lifetime
    tests of the rubber-metal-elements, three measurement quantities are acquired.
    Thereby, temperature is identified as the most suitable measurement quantity to
    describe the rubber-metal-elements state. The accuracy of a condition monitoring
    system is generally influenced by various uncertainties. To consider available
    uncertainties within the behavior and the degradation of the elements, the particle
    filter, a state-of-the-art model-based method for predicting remaining useful
    life, is enhanced and employed. The results prove that the developed condition
    monitoring system enables an increased utilization of rubber-metal-elements in
    real applications through predictive maintenance. This thesis provides the basis
    for future concepts of predictive maintenance for rubber-metal-elements. Moreover,
    it is recommended to take uncertainties into account at an early stage of the
    development process of condition monitoring systems.
author:
- first_name: Amelie
  full_name: Bender, Amelie
  id: '54290'
  last_name: Bender
citation:
  ama: Bender A. <i>Zustandsüberwachung zur Prognose der Restlebensdauer von Gummi-Metall-Elementen
    unter Berücksichtigung systembasierter Unsicherheiten</i>. Shaker; 2021. doi:<a
    href="https://doi.org/10.17619/UNIPB/1-1084">10.17619/UNIPB/1-1084</a>
  apa: Bender, A. (2021). <i>Zustandsüberwachung zur Prognose der Restlebensdauer
    von Gummi-Metall-Elementen unter Berücksichtigung systembasierter Unsicherheiten</i>.
    Shaker. <a href="https://doi.org/10.17619/UNIPB/1-1084">https://doi.org/10.17619/UNIPB/1-1084</a>
  bibtex: '@book{Bender_2021, title={Zustandsüberwachung zur Prognose der Restlebensdauer
    von Gummi-Metall-Elementen unter Berücksichtigung systembasierter Unsicherheiten},
    DOI={<a href="https://doi.org/10.17619/UNIPB/1-1084">10.17619/UNIPB/1-1084</a>},
    publisher={Shaker}, author={Bender, Amelie}, year={2021} }'
  chicago: Bender, Amelie. <i>Zustandsüberwachung zur Prognose der Restlebensdauer
    von Gummi-Metall-Elementen unter Berücksichtigung systembasierter Unsicherheiten</i>.
    Shaker, 2021. <a href="https://doi.org/10.17619/UNIPB/1-1084">https://doi.org/10.17619/UNIPB/1-1084</a>.
  ieee: A. Bender, <i>Zustandsüberwachung zur Prognose der Restlebensdauer von Gummi-Metall-Elementen
    unter Berücksichtigung systembasierter Unsicherheiten</i>. Shaker, 2021.
  mla: Bender, Amelie. <i>Zustandsüberwachung zur Prognose der Restlebensdauer von
    Gummi-Metall-Elementen unter Berücksichtigung systembasierter Unsicherheiten</i>.
    Shaker, 2021, doi:<a href="https://doi.org/10.17619/UNIPB/1-1084">10.17619/UNIPB/1-1084</a>.
  short: A. Bender, Zustandsüberwachung zur Prognose der Restlebensdauer von Gummi-Metall-Elementen
    unter Berücksichtigung systembasierter Unsicherheiten, Shaker, 2021.
date_created: 2021-04-15T10:29:53Z
date_updated: 2023-09-15T12:22:50Z
department:
- _id: '151'
doi: 10.17619/UNIPB/1-1084
keyword:
- Zustandsüberwachung
- Prognose der Restlebensdauer
- modellbasierte Prognose
- Partikelfilter
- Unsicherheiten
- Gummi
- Verlässlichkeit
- Lebensdauerversuche
- Predictive Maintenance
language:
- iso: ger
publisher: Shaker
status: public
supervisor:
- first_name: Walter
  full_name: Sextro, Walter
  id: '21220'
  last_name: Sextro
- first_name: Stefan
  full_name: Bracke, Stefan
  last_name: Bracke
title: Zustandsüberwachung zur Prognose der Restlebensdauer von Gummi-Metall-Elementen
  unter Berücksichtigung systembasierter Unsicherheiten
type: dissertation
user_id: '210'
year: '2021'
...
---
_id: '27111'
abstract:
- lang: eng
  text: In the industry 4.0 era, there is a growing need to transform unstructured
    data acquired by a multitude of sources into information and subsequently into
    knowledge to improve the quality of manufactured products, to boost production,
    for predictive maintenance, etc. Data-driven approaches, such as machine learning
    techniques, are typically employed to model the underlying relationship from data.
    However, an increase in model accuracy with state-of-the-art methods, such as
    deep convolutional neural networks, results in less interpretability and transparency.
    Due to the ease of implementation, interpretation and transparency to both domain
    experts and non-experts, a rule-based method is proposed in this paper, for prognostics
    and health management (PHM) and specifically for diagnostics. The proposed method
    utilizes the most relevant sensor signals acquired via feature extraction and
    selection techniques and expert knowledge. As a case study, the presented method
    is evaluated on data from a real-world quality control set-up provided by the
    European prognostics and health management society (PHME) at the conference’s
    2021 data challenge. With the proposed method, our team took the third place,
    capable of successfully diagnosing different fault modes, irrespective of varying
    conditions.
author:
- first_name: Osarenren Kennedy
  full_name: Aimiyekagbon, Osarenren Kennedy
  id: '9557'
  last_name: Aimiyekagbon
- first_name: Lars
  full_name: Muth, Lars
  id: '77313'
  last_name: Muth
  orcid: 0000-0002-2938-5616
- first_name: Meike Claudia
  full_name: Wohlleben, Meike Claudia
  id: '43991'
  last_name: Wohlleben
  orcid: 0009-0009-9767-7168
- first_name: Amelie
  full_name: Bender, Amelie
  id: '54290'
  last_name: Bender
- first_name: Walter
  full_name: Sextro, Walter
  id: '21220'
  last_name: Sextro
citation:
  ama: 'Aimiyekagbon OK, Muth L, Wohlleben MC, Bender A, Sextro W. Rule-based Diagnostics
    of a Production Line. In: Do P, King S, Fink O, eds. <i>Proceedings of the European
    Conference of the PHM Society 2021</i>. Vol 6. ; 2021:527-536. doi:<a href="https://doi.org/10.36001/phme.2021.v6i1.3042">10.36001/phme.2021.v6i1.3042</a>'
  apa: Aimiyekagbon, O. K., Muth, L., Wohlleben, M. C., Bender, A., &#38; Sextro,
    W. (2021). Rule-based Diagnostics of a Production Line. In P. Do, S. King, &#38;
    O. Fink (Eds.), <i>Proceedings of the European Conference of the PHM Society 2021</i>
    (Vol. 6, Issue 1, pp. 527–536). <a href="https://doi.org/10.36001/phme.2021.v6i1.3042">https://doi.org/10.36001/phme.2021.v6i1.3042</a>
  bibtex: '@inproceedings{Aimiyekagbon_Muth_Wohlleben_Bender_Sextro_2021, title={Rule-based
    Diagnostics of a Production Line}, volume={6}, DOI={<a href="https://doi.org/10.36001/phme.2021.v6i1.3042">10.36001/phme.2021.v6i1.3042</a>},
    number={1}, booktitle={Proceedings of the European Conference of the PHM Society
    2021}, author={Aimiyekagbon, Osarenren Kennedy and Muth, Lars and Wohlleben, Meike
    Claudia and Bender, Amelie and Sextro, Walter}, editor={Do, Phuc and King, Steve
    and Fink, Olga}, year={2021}, pages={527–536} }'
  chicago: Aimiyekagbon, Osarenren Kennedy, Lars Muth, Meike Claudia Wohlleben, Amelie
    Bender, and Walter Sextro. “Rule-Based Diagnostics of a Production Line.” In <i>Proceedings
    of the European Conference of the PHM Society 2021</i>, edited by Phuc Do, Steve
    King, and Olga Fink, 6:527–36, 2021. <a href="https://doi.org/10.36001/phme.2021.v6i1.3042">https://doi.org/10.36001/phme.2021.v6i1.3042</a>.
  ieee: 'O. K. Aimiyekagbon, L. Muth, M. C. Wohlleben, A. Bender, and W. Sextro, “Rule-based
    Diagnostics of a Production Line,” in <i>Proceedings of the European Conference
    of the PHM Society 2021</i>, 2021, vol. 6, no. 1, pp. 527–536, doi: <a href="https://doi.org/10.36001/phme.2021.v6i1.3042">10.36001/phme.2021.v6i1.3042</a>.'
  mla: Aimiyekagbon, Osarenren Kennedy, et al. “Rule-Based Diagnostics of a Production
    Line.” <i>Proceedings of the European Conference of the PHM Society 2021</i>,
    edited by Phuc Do et al., vol. 6, no. 1, 2021, pp. 527–36, doi:<a href="https://doi.org/10.36001/phme.2021.v6i1.3042">10.36001/phme.2021.v6i1.3042</a>.
  short: 'O.K. Aimiyekagbon, L. Muth, M.C. Wohlleben, A. Bender, W. Sextro, in: P.
    Do, S. King, O. Fink (Eds.), Proceedings of the European Conference of the PHM
    Society 2021, 2021, pp. 527–536.'
conference:
  name: PHM Society European Conference
date_created: 2021-11-03T12:26:39Z
date_updated: 2023-09-22T09:13:01Z
department:
- _id: '151'
doi: 10.36001/phme.2021.v6i1.3042
editor:
- first_name: Phuc
  full_name: Do, Phuc
  last_name: Do
- first_name: Steve
  full_name: King, Steve
  last_name: King
- first_name: Olga
  full_name: Fink, Olga
  last_name: Fink
intvolume: '         6'
issue: '1'
keyword:
- PHME 2021
- Feature Selection Classification
- Feature Selection Clustering
- Interpretable Model
- Transparent Model
- Industry 4.0
- Real-World Diagnostics
- Quality Control
- Predictive Maintenance
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: http://papers.phmsociety.org/index.php/phme/article/download/3042/1812
oa: '1'
page: 527-536
publication: Proceedings of the European Conference of the PHM Society 2021
publication_status: published
quality_controlled: '1'
status: public
title: Rule-based Diagnostics of a Production Line
type: conference
user_id: '9557'
volume: 6
year: '2021'
...
---
_id: '9949'
abstract:
- lang: eng
  text: Intelligent mechatronic systems other the possibility to adapt system behavior
    to current dependability. This can be used to assure reliability by controlling
    system behavior to reach a pre-defined lifetime. By using such closed loop control,
    the margin of error of useful lifetime of an individual system is lowered. It
    is also possible to change the pre-defined lifetime during operation, by adapting
    system behavior to derate component usage. When planning maintenance actions,
    the remaining useful lifetime of each individual system has to be taken into account.
    Usually, stochastic properties of a fleet of systems are analyzed to create maintenance
    plans. Among these, the main factor is the probability of an individual system
    to last until maintenance. If condition-based maintenance is used, this is updated
    for each individual system using available information about its current state.
    By lowering the margin of error of useful lifetime, which directly corresponds
    to the time until maintenance, extended maintenance periods are made possible.
    Also using reliability-adaptive operation, a reversal of degradation driven maintenance
    planning is possible where a maintenance plan is setup not only according to system
    properties, but mainly to requirements imposed by maintenance personnel or infrastructure.
    Each system then adapts its behavior accordingly and fails according to the maintenance
    plan, making better use of maintenance personnel and system capabilities at the
    same time. In this contribution, the potential of maintenance plan driven system
    behavior adaptation is shown. A model including adaptation process and maintenance
    actions is simulated over full system lifetime to assess the advantages gained.
author:
- first_name: Tobias
  full_name: Meyer, Tobias
  last_name: Meyer
- first_name: Thorben
  full_name: Kaul, Thorben
  id: '14802'
  last_name: Kaul
- first_name: Walter
  full_name: Sextro, Walter
  id: '21220'
  last_name: Sextro
citation:
  ama: 'Meyer T, Kaul T, Sextro W. Advantages of reliability-adaptive system operation
    for maintenance planning. In: <i>Proceedings of the 9th IFAC Symposium on Fault
    Detection, Supervision and Safety for Technical Processes</i>. ; 2015:940-945.
    doi:<a href="https://doi.org/10.1016/j.ifacol.2015.09.647">10.1016/j.ifacol.2015.09.647</a>'
  apa: Meyer, T., Kaul, T., &#38; Sextro, W. (2015). Advantages of reliability-adaptive
    system operation for maintenance planning. In <i>Proceedings of the 9th IFAC Symposium
    on Fault Detection, Supervision and Safety for Technical Processes</i> (pp. 940–945).
    <a href="https://doi.org/10.1016/j.ifacol.2015.09.647">https://doi.org/10.1016/j.ifacol.2015.09.647</a>
  bibtex: '@inproceedings{Meyer_Kaul_Sextro_2015, title={Advantages of reliability-adaptive
    system operation for maintenance planning}, DOI={<a href="https://doi.org/10.1016/j.ifacol.2015.09.647">10.1016/j.ifacol.2015.09.647</a>},
    booktitle={Proceedings of the 9th IFAC Symposium on Fault Detection, Supervision
    and Safety for Technical Processes}, author={Meyer, Tobias and Kaul, Thorben and
    Sextro, Walter}, year={2015}, pages={940–945} }'
  chicago: Meyer, Tobias, Thorben Kaul, and Walter Sextro. “Advantages of Reliability-Adaptive
    System Operation for Maintenance Planning.” In <i>Proceedings of the 9th IFAC
    Symposium on Fault Detection, Supervision and Safety for Technical Processes</i>,
    940–45, 2015. <a href="https://doi.org/10.1016/j.ifacol.2015.09.647">https://doi.org/10.1016/j.ifacol.2015.09.647</a>.
  ieee: T. Meyer, T. Kaul, and W. Sextro, “Advantages of reliability-adaptive system
    operation for maintenance planning,” in <i>Proceedings of the 9th IFAC Symposium
    on Fault Detection, Supervision and Safety for Technical Processes</i>, 2015,
    pp. 940–945.
  mla: Meyer, Tobias, et al. “Advantages of Reliability-Adaptive System Operation
    for Maintenance Planning.” <i>Proceedings of the 9th IFAC Symposium on Fault Detection,
    Supervision and Safety for Technical Processes</i>, 2015, pp. 940–45, doi:<a href="https://doi.org/10.1016/j.ifacol.2015.09.647">10.1016/j.ifacol.2015.09.647</a>.
  short: 'T. Meyer, T. Kaul, W. Sextro, in: Proceedings of the 9th IFAC Symposium
    on Fault Detection, Supervision and Safety for Technical Processes, 2015, pp.
    940–945.'
date_created: 2019-05-27T08:29:40Z
date_updated: 2019-09-16T10:43:42Z
department:
- _id: '151'
doi: 10.1016/j.ifacol.2015.09.647
keyword:
- Adaptive systems
- Reliability analysis
- Availability
- Adaptive control
- Maintenance
- Self-optimizing systems
- Self-optimizing control
- Stochastic Petri-nets
language:
- iso: eng
page: 940-945
publication: Proceedings of the 9th IFAC Symposium on Fault Detection, Supervision
  and Safety for Technical Processes
quality_controlled: '1'
status: public
title: Advantages of reliability-adaptive system operation for maintenance planning
type: conference
user_id: '55222'
year: '2015'
...
---
_id: '9808'
abstract:
- lang: eng
  text: This study presents the methods employed by a team from the department of
    Mechatronics and Dynamics at the University of Paderborn, Germany for the 2013
    PHM data challenge. The focus of the challenge was on maintenance action recommendation
    for an industrial machinery based on remote monitoring and diagnosis. Since an
    ensemble of data driven methods has been considered as the state of the art approach
    in diagnosis and prognosis, the first approach was to evaluate the performance
    of an ensemble of data driven methods using the parametric data as input and problems
    (recommended maintenance action) as the output. Due to close correlation of parametric
    data of different problems, this approach produced high misclassification rate.
    Event-based decision trees were then constructed to identify problems associated
    with particular events. To distinguish between problems associated with events
    that appeared in multiple problems, support vector machine (SVM) with parameters
    optimally tuned using particle swarm optimization (PSO) was employed. Parametric
    data was used as the input to the SVM algorithm and majority voting was employed
    to determine the final decision for cases with multiple events. A total of 165
    SVM models were constructed. This approach improved the overall score from 21
    to 48. The method was further enhanced by employing an ensemble of three data
    driven methods, that is, SVM, random forests (RF) and bagged trees (BT), to build
    the event based models. With this approach, a score of 51 was obtained . The results
    demonstrate that the proposed event based method can be effective in maintenance
    action recommendation based on events codes and parametric data acquired remotely
    from an industrial equipment.
author:
- first_name: James Kuria
  full_name: Kimotho, James Kuria
  last_name: Kimotho
- first_name: Chritoph
  full_name: Sondermann-Wölke, Chritoph
  last_name: Sondermann-Wölke
- first_name: Tobias
  full_name: Meyer, Tobias
  last_name: Meyer
- first_name: Walter
  full_name: Sextro, Walter
  id: '21220'
  last_name: Sextro
citation:
  ama: Kimotho JK, Sondermann-Wölke C, Meyer T, Sextro W. Application of Event Based
    Decision Tree and Ensemble of Data Driven Methods for Maintenance Action Recommendation.
    <i>International Journal of Prognostics and Health Management</i>. 2013;4(2).
  apa: Kimotho, J. K., Sondermann-Wölke, C., Meyer, T., &#38; Sextro, W. (2013). Application
    of Event Based Decision Tree and Ensemble of Data Driven Methods for Maintenance
    Action Recommendation. <i>International Journal of Prognostics and Health Management</i>,
    <i>4</i>(2).
  bibtex: '@article{Kimotho_Sondermann-Wölke_Meyer_Sextro_2013, title={Application
    of Event Based Decision Tree and Ensemble of Data Driven Methods for Maintenance
    Action Recommendation}, volume={4}, number={2}, journal={International Journal
    of Prognostics and Health Management}, author={Kimotho, James Kuria and Sondermann-Wölke,
    Chritoph and Meyer, Tobias and Sextro, Walter}, year={2013} }'
  chicago: Kimotho, James Kuria, Chritoph Sondermann-Wölke, Tobias Meyer, and Walter
    Sextro. “Application of Event Based Decision Tree and Ensemble of Data Driven
    Methods for Maintenance Action Recommendation.” <i>International Journal of Prognostics
    and Health Management</i> 4, no. 2 (2013).
  ieee: J. K. Kimotho, C. Sondermann-Wölke, T. Meyer, and W. Sextro, “Application
    of Event Based Decision Tree and Ensemble of Data Driven Methods for Maintenance
    Action Recommendation,” <i>International Journal of Prognostics and Health Management</i>,
    vol. 4, no. 2, 2013.
  mla: Kimotho, James Kuria, et al. “Application of Event Based Decision Tree and
    Ensemble of Data Driven Methods for Maintenance Action Recommendation.” <i>International
    Journal of Prognostics and Health Management</i>, vol. 4, no. 2, 2013.
  short: J.K. Kimotho, C. Sondermann-Wölke, T. Meyer, W. Sextro, International Journal
    of Prognostics and Health Management 4 (2013).
date_created: 2019-05-13T14:15:36Z
date_updated: 2022-01-06T07:04:21Z
department:
- _id: '151'
intvolume: '         4'
issue: '2'
keyword:
- maintenance decision
- Bagged trees
- Decision trees
- PSO-SVM
- Random forests
language:
- iso: eng
publication: International Journal of Prognostics and Health Management
quality_controlled: '1'
status: public
title: Application of Event Based Decision Tree and Ensemble of Data Driven Methods
  for Maintenance Action Recommendation
type: journal_article
user_id: '55222'
volume: 4
year: '2013'
...