---
_id: '9994'
abstract:
- lang: eng
text: Reliability-adaptive systems allow an adaptation of system behavior based
on current system reliability. They can extend their lifetime at the cost of lowered
performance or vice versa. This can be used to adapt failure behavior according
to a maintenance plan, thus increasing availability while using up system capability
fully. To facilitate setup, a control algorithm independent of a degradation model
is desired. A closed loop control technique for reliability based on a health
index, a measure for system degradation, is introduced. It uses self-optimization
as means to implement behavior adaptation. This is based on selecting the priorities
of objectives that the system pursues. Possible working points are computed beforehand
using model-based multiobjective optimization techniques. The controller selects
the priorities of objectives and this way balances reliability and performance.
As exemplary application, an automatically actuated single plate dry clutch is
introduced. The entire reliability control is setup and lifetime experiments are
conducted. Results show that the variance of time to failure is reduced greatly,
making the failure behavior more predictable. At the same time, the desired usable
lifetime can be extended at the cost of system performance to allow for changed
maintenance intervals. Together, these possibilities allow for greater system
usage and better planning of maintenance.
author:
- first_name: Tobias
full_name: Meyer, Tobias
last_name: Meyer
citation:
ama: Meyer T. Optimization-Based Reliability Control of Mechatronic Systems.
Shaker; 2018.
apa: Meyer, T. (2018). Optimization-based reliability control of mechatronic
systems. Shaker.
bibtex: '@book{Meyer_2018, title={Optimization-based reliability control of mechatronic
systems}, publisher={Shaker}, author={Meyer, Tobias}, year={2018} }'
chicago: Meyer, Tobias. Optimization-Based Reliability Control of Mechatronic
Systems. Shaker, 2018.
ieee: T. Meyer, Optimization-based reliability control of mechatronic systems.
Shaker, 2018.
mla: Meyer, Tobias. Optimization-Based Reliability Control of Mechatronic Systems.
Shaker, 2018.
short: T. Meyer, Optimization-Based Reliability Control of Mechatronic Systems,
Shaker, 2018.
date_created: 2019-05-27T10:21:17Z
date_updated: 2023-09-15T12:26:09Z
department:
- _id: '151'
keyword:
- dependability
- reliability
- behavior adaptation
- self-optimization
- multiobjective optimization
- optimal control
- automotive drivetrain
- clutch system
- reliability-adaptive system
language:
- iso: eng
publisher: Shaker
status: public
title: Optimization-based reliability control of mechatronic systems
type: dissertation
user_id: '210'
year: '2018'
...
---
_id: '9885'
abstract:
- lang: eng
text: Intelligent mechatronic systems, such as self-optimizing systems, allow an
adaptation of the system behavior at runtime based on the current situation. To
do so, they generally select among several pre-defined working points. A common
method to determine working points for a mechatronic system is to use model-based
multiobjective optimization. It allows finding compromises among conflicting objectives,
called objective functions, by adapting parameters. To evaluate the system behavior
for different parameter sets, a model of the system behavior is included in the
objective functions and is evaluated during each function call. Intelligent mechatronic
systems also have the ability to adapt their behavior based on their current reliability,
thus increasing their availability, or on changed safety requirements; all of
which are summed up by the common term dependability. To allow this adaptation,
dependability can be considered in multiobjective optimization by including dependability-related
objective functions. However, whereas performance-related objective functions
are easily found, formulation of dependability-related objective functions is
highly system-specific and not intuitive, making it complex and error-prone. Since
each mechatronic system is different, individual failure modes have to be taken
into account, which need to be found using common methods such as Failure-Modes
and Effects Analysis or Fault Tree Analysis. Using component degradation models,
which again are specific to the system at hand, the main loading factors can be
determined. By including these in the model of the system behavior, the relation
between working point and dependability can be formulated as an objective function.
In our work, this approach is presented in more detail. It is exemplified using
an actively actuated single plate dry clutch system. Results show that this approach
is suitable for formulating dependability-related objective functions and that
these can be used to extend system lifetime by adapting system behavior.
author:
- first_name: Tobias
full_name: Meyer , Tobias
last_name: 'Meyer '
- first_name: Christoph
full_name: Sondermann-Wölke, Christoph
last_name: Sondermann-Wölke
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: Meyer T, Sondermann-Wölke C, Sextro W. Method to Identify Dependability Objectives
in Multiobjective Optimization Problem. Conference Proceedings of the 2nd International
Conference on System-Integrated Intelligence. 2014;15:46-53. doi:10.1016/j.protcy.2014.09.033
apa: Meyer , T., Sondermann-Wölke, C., & Sextro, W. (2014). Method to Identify
Dependability Objectives in Multiobjective Optimization Problem. Conference
Proceedings of the 2nd International Conference on System-Integrated Intelligence,
15, 46–53. https://doi.org/10.1016/j.protcy.2014.09.033
bibtex: '@article{Meyer _Sondermann-Wölke_Sextro_2014, title={Method to Identify
Dependability Objectives in Multiobjective Optimization Problem}, volume={15},
DOI={10.1016/j.protcy.2014.09.033},
journal={Conference Proceedings of the 2nd International Conference on System-Integrated
Intelligence}, author={Meyer , Tobias and Sondermann-Wölke, Christoph and Sextro,
Walter}, year={2014}, pages={46–53} }'
chicago: 'Meyer , Tobias, Christoph Sondermann-Wölke, and Walter Sextro. “Method
to Identify Dependability Objectives in Multiobjective Optimization Problem.”
Conference Proceedings of the 2nd International Conference on System-Integrated
Intelligence 15 (2014): 46–53. https://doi.org/10.1016/j.protcy.2014.09.033.'
ieee: T. Meyer , C. Sondermann-Wölke, and W. Sextro, “Method to Identify Dependability
Objectives in Multiobjective Optimization Problem,” Conference Proceedings
of the 2nd International Conference on System-Integrated Intelligence, vol.
15, pp. 46–53, 2014.
mla: Meyer , Tobias, et al. “Method to Identify Dependability Objectives in Multiobjective
Optimization Problem.” Conference Proceedings of the 2nd International Conference
on System-Integrated Intelligence, vol. 15, 2014, pp. 46–53, doi:10.1016/j.protcy.2014.09.033.
short: T. Meyer , C. Sondermann-Wölke, W. Sextro, Conference Proceedings of the
2nd International Conference on System-Integrated Intelligence 15 (2014) 46–53.
date_created: 2019-05-20T13:19:37Z
date_updated: 2019-09-16T10:22:04Z
department:
- _id: '151'
doi: 10.1016/j.protcy.2014.09.033
intvolume: ' 15'
keyword:
- Self-optimization
- multiobjective optimization
- objective function
- dependability
- intelligent system
- behavior adaptation
language:
- iso: eng
page: 46-53
publication: Conference Proceedings of the 2nd International Conference on System-Integrated
Intelligence
quality_controlled: '1'
status: public
title: Method to Identify Dependability Objectives in Multiobjective Optimization
Problem
type: journal_article
user_id: '55222'
volume: 15
year: '2014'
...