---
res:
  bibo_abstract:
  - 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.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Tobias
      foaf_name: Meyer , Tobias
      foaf_surname: 'Meyer '
  - foaf_Person:
      foaf_givenName: Christoph
      foaf_name: Sondermann-Wölke, Christoph
      foaf_surname: Sondermann-Wölke
  - foaf_Person:
      foaf_givenName: Walter
      foaf_name: Sextro, Walter
      foaf_surname: Sextro
      foaf_workInfoHomepage: http://www.librecat.org/personId=21220
  bibo_doi: 10.1016/j.protcy.2014.09.033
  bibo_volume: 15
  dct_date: 2014^xs_gYear
  dct_language: eng
  dct_subject:
  - Self-optimization
  - multiobjective optimization
  - objective function
  - dependability
  - intelligent system
  - behavior adaptation
  dct_title: Method to Identify Dependability Objectives in Multiobjective Optimization
    Problem@
...