@inproceedings{9791,
  abstract     = {{The rapid development of communication and information technology opens up fascinating perspectives, which go far beyond the state of the art in mechatronics: mechatronic systems with inherent partial intelligence. These so called self-optimizing systems adapt their objectives and behavior autonomously and flexibly to changing operating conditions. On the one hand, securing the dependability of such systems is challenging due to their complexity and non-deterministic behavior. On the other hand, self-optimization can be used to increase the dependability of the system during its operation. However, it has to be ensured, that the self-optimization works dependable itself. To cope with these challenges, the multi-level dependability concept was developed. It enables predictive condition monitoring, influences the objectives of the system and determines suitable means to improve the system's dependability during its operation. In this contribution we introduce a procedure for the conceptual design of an advanced condition monitoring based on the system's principle solution. The principle solution describes the principal operation mode of the system and its desired behavior. It is modeled using the specification technique for the domain-spanning description of the principle solution of a self-optimizing system and consists of a coherent system of eight partial models (e.g. requirements, active structure, system of objectives, behavior, etc.). The partial models are analyzed separately in order to derive the components of the multi-level dependability concept. In particular, the reliability analysis of the partial model active structure is performed to identify the system elements to be monitored and parameters to be measured. The principle solution is extended accordingly: e.g. with system elements required for the realization of the dependability concept. The advantages of the method are shown on the self-optimizing guidance module of a railroad vehicle.}},
  author       = {{Sondermann-Wölke , Christoph and Meyer, Tobias and Dorociak, Rafal and Gausemeier, Jürgen and Sextro, Walter}},
  booktitle    = {{Proceedings of the 11th International Probabilistic Safety Assessment and Management Conference (PSAM11) and The Annual European Safety and Reliability Conference (ESREL2012)}},
  keywords     = {{Mechatronic Systems, Principle Solution, Condition Monitoring, Conceptual Design}},
  title        = {{{Conceptual Design of Advanced Condition Monitoring for a Self-Optimizing System based on its Principle Solution}}},
  year         = {{2012}},
}

@inproceedings{9736,
  abstract     = {{Self-optimizing mechatronic systems are a new class of technical systems. On the one hand, new challenges regarding dependability arise from their additional complexity and adaptivity. On the other hand, their abilities enable new concepts and methods to improve the dependability of mechatronic systems. This paper introduces a multi-level dependability concept for self-optimizing mechatronic systems and shows how planning can be used to improve the availability and reliability of systems in the operating stages.}},
  author       = {{Klöpper, Benjamin and Sondermann-Wölke, Christoph and Romaus, Christoph and Vöcking, Henner}},
  booktitle    = {{Computational Intelligence in Control and Automation, 2009. CICA 2009. IEEE Symposium on}},
  keywords     = {{multilevel dependability concept, probabilistic planning, self-optimizing mechatronic systems, systems reliability, mechatronics, planning (artificial intelligence), self-adjusting systems}},
  pages        = {{104 --111}},
  title        = {{{Probabilistic planning integrated in a multi-level dependability concept for mechatronic systems}}},
  doi          = {{10.1109/CICA.2009.4982790}},
  year         = {{2009}},
}

@inproceedings{9742,
  abstract     = {{New mechatronic systems, called self-optimizing systems, are able to adapt their behavior according to environmental, user and system specific influences. Self-optimizing systems are complex and due to their non-deterministic behavior comprise hidden risks, which cannot be foreseen in the design phase of the system. Therefore, this paper presents modifications of the current condition monitoring policy, to be able to cope with this new kind of systems. Beside avoiding critical situations evoked by self-optimization, the proposed concept uses self-optimization to increase the dependability of the system. In this case, the concept is applied to the active guidance module of an innovative rail-bound vehicle.}},
  author       = {{Sondermann-Wölke, Christoph and Sextro, Walter}},
  booktitle    = {{Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns, 2009. COMPUTATIONWORLD '09. Computation World:}},
  keywords     = {{condition monitoring, mechatronic systems, rail bound vehicle, rail guidance module, self-optimization, self-optimizing function modules, condition monitoring, mechatronics, railway rolling stock, self-adjusting systems}},
  pages        = {{15 --20}},
  title        = {{{Towards the Integration of Condition Monitoring in Self-Optimizing Function Modules}}},
  doi          = {{10.1109/ComputationWorld.2009.47}},
  year         = {{2009}},
}

@inproceedings{39078,
  author       = {{Gausemeier, Jürgen and Müller, Wolfgang and Paelke, Volker and Bauch, Jürgen and Shen, Q. and Radkowski, R. }},
  booktitle    = {{Proceedings of the Design 2004}},
  keywords     = {{mechatronic systems, self-optimization, virtual prototyping}},
  location     = {{Dubrovnik}},
  title        = {{{Virtual Prototyping Of Self-Optimizing Mechatronic Systems}}},
  year         = {{2004}},
}