Motivation and objectives
The definition of regeneration paths for complex capital goods, as well as the decision for the optimal regeneration path are connected with partly considerable uncertainties. These are reflected as risks for the overall success of the regeneration. A regeneration path must be defined in such a way that both technical and economic risks of regeneration are kept to a minimum. At the same time, past and intended conditions of use for the capital good determine requirements for regeneration, which are to be quantified by mapping all uncertainties on the functionality of the capital good as an overall system. Ultimately, resilience in the regeneration path should ensure that unforeseen deviations from the planned regeneration can be cushioned with minimal effort and risk by adjusting the regeneration path. In the interaction of these aspects, sub-project D5 will support the definition of regeneration paths with an optimal balance between investment and acceptable risk with quantitative statements on risks and resilience.
Results
In the second funding period, basic scientific and technological solutions were developed which mainly quantify aleatoric uncertainties, i.e. uncertainties resulting from random influences during repair and in material quality, and which show themselves as stochastic properties in the functional behaviour of components of capital goods. Thus the primary technical risk can be estimated that the capital goods do not reach the intended quality as a function of time, expressed by the required reliability and service life. Specifically, a function-based system model was developed using the example of the regeneration of an axial compressor in close cooperation with sub-projects B3 and C6.
Current research and outlook
In the third funding period of the SFB, research in sub-project D5 aims at an integral algorithm for the risk assessment of the regeneration paths, and for the support of resilient regeneration with a focus on the functionality of the entire engine. By selecting a robust and reliable regeneration path, both technical and economic risks should be minimized. The scientific and technological basic solutions developed in the previous funding period are used as a basis in order to comprehensively consider uncertainties and risks in the regeneration of complex capital goods. In particular, the numerical model developed for the reliability analysis of capital goods will be used as a basis. The long-term questions formulated for the subproject can be specified as follows for the funding period applied for:
- What quality of regeneration is necessary to keep the risks of individual regeneration paths acceptable?
- How can risk-driving combinations of low-risk regeneration steps be identified and avoided in detail?
- How robust are the regeneration paths with regard to unforeseen deviations in the functional properties of the components during regeneration?
- How can subsequent decisions be adapted during regeneration to compensate for risk if critical deviations from the target quality occur?
- How can resilience of the regeneration processes be maximized already during their planning, so that risk-compensating corrections in the regeneration paths are minimally invasive.
The general validity of the theories and methods ensures transferability to other, especially stationary capital goods, such as parts of power plants and wind turbines.
Subproject leader
30167 Hannover
30167 Hannover
Staff
30167 Hannover
Publications
International Scientific Journal Paper, peer-reviewed
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(2021): Efficient reliability analysis of complex systems in consideration of imprecision., Reliability Engineering & System Safety 216 (2), S. 107972
DOI: 10.1016/j.ress.2021.107972 -
(2020): Resilience Decision-Making for Complex Systems, ASME J. Risk Uncertainty Part B. Jun 2020, 6(2): 020901
DOI: 10.1115/1.4044907 -
(2019): Reliability Analysis of an Axial Compressor Based on One-Dimensional Flow Modeling and Survival Signature., ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems,Part B: Mechanical Engineering SEPTEMBER 2019, Vol. 5, 031003-1 - 031003-9
DOI: 10.1115/1.4043150. -
(2019): Resilience Decision-Making For Complex Systems, The ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
DOI: 10.1115/1.4044907
International Conference Paper, peer-reviewed
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(2020): Efficient Reliability Analysis of an Axial Compressor in Consideration of Epistemic Uncertainty, Piero Baraldi, Francesco Di Maio und Enrico Zio (Hg.): Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference
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(2019): Multidimensional Resilience Decision-Making On A Multistage High-Speed Axial Compressor, Beer, M. und Zio, E. (Hg.): Proceedings of the 29th European Safety and Reliability Conference (ESREL 2019), 22-26 September, Hannover, DE., S. 1357–1364
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(2018): Decision-Making for Resilience-Enhancing Endowments in Complex Systems using Principles of Risk Measures, Proc. of the 6th Intl. Symposium on Reliability Engineering and RiskManagement (6ISRERM)Resilience and Sustainability of Urban Systems.
DOI: 10.3850/978-981-11-2726-7_CRR06 -
(2017): Survival signature approach for the reliability analysis of an axial compressor., In: Cepin, M. et al. (eds.) Safety and Reliability – Theory and Application: ESREL 2017, Proceedings of the European Safety and Reliability Conference (ESREL 2017), Taylor & Francis Group, London.
