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Cyber-Physical Systems – future-oriented technological synergies

A Cyber-Physical System (CPS) utilises sensor data of various sources, integrated intelligence, and a communication network, for instance, for predicting the health state of critical components or systems of an aircraft fleet and for directing necessary MRO actions at an early stage. The key question, for which business problems cost-saving potentials emerge with respect to conventional maintenance strategies, was examined at Bauhaus Luftfahrt in the framework of future technology analysis.

By means of Machine Learning and Big Data Analytics, a CPS can significantly reduce previous uncertainties in failure prediction by capturing complex relationships in fleet-wide data that may be difficult to describe using physics. Examples include the correlation between operating environment or repair actions and degradation rate. However, in case, relative to correctly predicted maintenance needs, missed detections or false alarms occur too often, follow-up costs, e. g. due to cascading effects or unnecessary inspection effort, can outweigh the advantages, similarly to CPS costs. The requirements on the prediction quality for achieving a net benefit strongly depend on the application. They were generally determined at Bauhaus Luftfahrt by means of a Cost-Benefit Analysis. It further allows comparing and optimising various analysis algorithms concerning cost efficiency. Here, for instance, for bearing and gearbox monitoring or crack detection in composites, deep learning approaches appear most promising. For realising the full potential, new directives for data exchange, privacy, and cyber security are in demand.

Future CPS visions include the exploitation of product-specific data along the life cycle for novel business models, such as individualised production and maintenance or virtual digital certification.

  • Working principle of a CPS: A CPS promotes system-relevant sensory data, such as for fleet monitoring, into actionable information for decision support and optimised system control, e. g. allowing for reduced downtime and MRO costs.Working principle of a CPS: A CPS promotes system-relevant sensory data, such as for fleet monitoring, into actionable information for decision support and optimised system control, e. g. allowing for reduced downtime and MRO costs.
  • CPS Cost-benefit analysis: The receiver operating characteristics curve can be directly linked with cost-benefit analysis for performance assessment and optimisation of data analysis algorithms and for identifying business cases with net benefit.CPS Cost-benefit analysis: The receiver operating characteristics curve can be directly linked with cost-benefit analysis for performance assessment and optimisation of data analysis algorithms and for identifying business cases with net benefit.