---
_id: '9976'
abstract:
- lang: eng
text: State-of-the-art mechatronic systems offer inherent intelligence that enables
them to autonomously adapt their behavior to current environmental conditions
and to their own system state. This autonomous behavior adaptation is made possible
by software in combination with complex sensor and actuator systems and by sophisticated
information processing, all of which make these systems increasingly complex.
This increasing complexity makes the design process a challenging task and brings
new complex possibilities for operation and maintenance. However, with the risk
of increased system complexity also comes the chance to adapt system behavior
based on current reliability, which in turn increases reliability. The development
of such an adaption strategy requires appropriate methods to evaluate reliability
based on currently selected system behavior. A common approach to implement such
adaptivity is to base system behavior on different working points that are obtained
using multiobjective optimization. During operation, selection among these allows
a changed operating strategy. To allow for multiobjective optimization, an accurate
system model including system reliability is required. This model is repeatedly
evaluated by the optimization algorithm. At present, modeling of system reliability
and synchronization of the models of behavior and reliability is a laborious manual
task and thus very error-prone. Since system behavior is crucial for system reliability,
an integrated model is introduced that integrates system behavior and system reliability.
The proposed approach is used to formulate reliability-related objective functions
for a clutch test rig that are used to compute feasible working points using multiobjective
optimization.
author:
- first_name: Thorben
full_name: Kaul, Thorben
id: '14802'
last_name: Kaul
- first_name: Tobias
full_name: Meyer, Tobias
last_name: Meyer
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: Kaul T, Meyer T, Sextro W. Formulation of reliability-related objective functions
for design of intelligent mechatronic systems. SAGE Journals. 2017;Vol.
231(4):390-399. doi:10.1177/1748006X17709376
apa: Kaul, T., Meyer, T., & Sextro, W. (2017). Formulation of reliability-related
objective functions for design of intelligent mechatronic systems. SAGE Journals,
Vol. 231(4), 390–399. https://doi.org/10.1177/1748006X17709376
bibtex: '@article{Kaul_Meyer_Sextro_2017, title={Formulation of reliability-related
objective functions for design of intelligent mechatronic systems}, volume={Vol.
231(4)}, DOI={10.1177/1748006X17709376},
journal={SAGE Journals}, author={Kaul, Thorben and Meyer, Tobias and Sextro, Walter},
year={2017}, pages={390–399} }'
chicago: 'Kaul, Thorben, Tobias Meyer, and Walter Sextro. “Formulation of Reliability-Related
Objective Functions for Design of Intelligent Mechatronic Systems.” SAGE Journals
Vol. 231(4) (2017): 390–99. https://doi.org/10.1177/1748006X17709376.'
ieee: T. Kaul, T. Meyer, and W. Sextro, “Formulation of reliability-related objective
functions for design of intelligent mechatronic systems,” SAGE Journals,
vol. Vol. 231(4), pp. 390–399, 2017.
mla: Kaul, Thorben, et al. “Formulation of Reliability-Related Objective Functions
for Design of Intelligent Mechatronic Systems.” SAGE Journals, vol. Vol.
231(4), 2017, pp. 390–99, doi:10.1177/1748006X17709376.
short: T. Kaul, T. Meyer, W. Sextro, SAGE Journals Vol. 231(4) (2017) 390–399.
date_created: 2019-05-27T09:37:46Z
date_updated: 2019-09-16T10:20:49Z
department:
- _id: '151'
doi: 10.1177/1748006X17709376
keyword:
- Integrated model
- reliability
- system behavior
- Bayesian network
- multiobjective optimization
language:
- iso: eng
page: 390 - 399
publication: SAGE Journals
quality_controlled: '1'
status: public
title: Formulation of reliability-related objective functions for design of intelligent
mechatronic systems
type: journal_article
user_id: '55222'
volume: Vol. 231(4)
year: '2017'
...
---
_id: '9763'
abstract:
- lang: eng
text: Recent advances in information processing enable new kinds of technical systems,
called self-optimizing systems. These systems are able to adapt their objectives
and their behavior according to the current situation and influences autonomously.
This behavior adaptation is non-deterministic and hence self-optimization is a
risk to the system, e.g. if the result of the self-optimization process does not
match the suddenly changed situation. In contrary, self-optimization could be
used to increase the dependability by pursuing objectives like reliability and
availability. In our preceding publications we introduced the so called multi-level
dependability concept to cope with this new kind of systems (cf. [6]). This concept
comprises the monitoring of the system behavior, the classification of the current
situation, and the selection of the appropriate measure, if reliability limits
are exceeded. In this paper we present for the first time experimental results.
The dependability concept is implemented in the self-optimizing active guidance
system of a railway vehicle. The test drives illustrate clearly that the proposed
concept is able to cope with, e.g., sensor failures, and is able to increase the
reliability and availability of the active guidance module.
author:
- first_name: Christoph
full_name: Sondermann-Wölke, Christoph
last_name: Sondermann-Wölke
- first_name: Jens
full_name: Geisler, Jens
last_name: Geisler
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Sondermann-Wölke C, Geisler J, Sextro W. Increasing the reliability of a self-optimizing
railway guidance system. In: Reliability and Maintainability Symposium (RAMS),
2010 Proceedings - Annual. ; 2010:1-6. doi:10.1109/RAMS.2010.5448080'
apa: Sondermann-Wölke, C., Geisler, J., & Sextro, W. (2010). Increasing the
reliability of a self-optimizing railway guidance system. In Reliability and
Maintainability Symposium (RAMS), 2010 Proceedings - Annual (pp. 1–6). https://doi.org/10.1109/RAMS.2010.5448080
bibtex: '@inproceedings{Sondermann-Wölke_Geisler_Sextro_2010, title={Increasing
the reliability of a self-optimizing railway guidance system}, DOI={10.1109/RAMS.2010.5448080},
booktitle={Reliability and Maintainability Symposium (RAMS), 2010 Proceedings
- Annual}, author={Sondermann-Wölke, Christoph and Geisler, Jens and Sextro, Walter},
year={2010}, pages={1–6} }'
chicago: Sondermann-Wölke, Christoph, Jens Geisler, and Walter Sextro. “Increasing
the Reliability of a Self-Optimizing Railway Guidance System.” In Reliability
and Maintainability Symposium (RAMS), 2010 Proceedings - Annual, 1–6, 2010.
https://doi.org/10.1109/RAMS.2010.5448080.
ieee: C. Sondermann-Wölke, J. Geisler, and W. Sextro, “Increasing the reliability
of a self-optimizing railway guidance system,” in Reliability and Maintainability
Symposium (RAMS), 2010 Proceedings - Annual, 2010, pp. 1–6.
mla: Sondermann-Wölke, Christoph, et al. “Increasing the Reliability of a Self-Optimizing
Railway Guidance System.” Reliability and Maintainability Symposium (RAMS),
2010 Proceedings - Annual, 2010, pp. 1–6, doi:10.1109/RAMS.2010.5448080.
short: 'C. Sondermann-Wölke, J. Geisler, W. Sextro, in: Reliability and Maintainability
Symposium (RAMS), 2010 Proceedings - Annual, 2010, pp. 1–6.'
date_created: 2019-05-13T10:35:39Z
date_updated: 2022-01-06T07:04:19Z
department:
- _id: '151'
doi: 10.1109/RAMS.2010.5448080
keyword:
- availability
- dependability concept
- multilevel dependability concept
- railway vehicle
- reliability
- self optimizing active guidance system
- self optimizing railway guidance system
- situation classification
- system behavior monitoring
- optimal control
- railways
- reliability theory
- self-adjusting systems
language:
- iso: eng
page: 1 -6
publication: Reliability and Maintainability Symposium (RAMS), 2010 Proceedings -
Annual
publication_identifier:
issn:
- 0149-144X
quality_controlled: '1'
status: public
title: Increasing the reliability of a self-optimizing railway guidance system
type: conference
user_id: '55222'
year: '2010'
...