A Model-Based Reliability Analysis Method Using Bayesian Network
dc.contributor.author | Kabir, Sohag | |
dc.contributor.author | Campean, Felician | |
dc.date.accessioned | 2021-12-10T17:31:25Z | |
dc.date.accessioned | 2021-12-22T16:30:18Z | |
dc.date.available | 2021-12-10T17:31:25Z | |
dc.date.available | 2021-12-22T16:30:18Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Kabir S and Campean IF (2022) A Model-Based Reliability Analysis Method Using Bayesian Network. In: Jansen T, Jensen R, Mac Parthaláin N, et al (Eds) Advances in Computational Intelligence Systems. UKCI 2021. Advances in Intelligent Systems and Computing. Vol 1409. Springer, Cham. | en_US |
dc.identifier.uri | http://hdl.handle.net/10454/18710 | |
dc.description | Yes | en_US |
dc.description.abstract | Bayesian Network (BN)-based methods are increasingly used in system reliability analysis. While BNs enable to perform multiple analyses based on a single model, the construction of robust BN models relies either on the conversion from other intermediate system model structures or direct analyst-led development based on experts input, both requiring significant human effort. This article proposes an architecture model-based approach for the direct generation of a BN model. Given the architectural model of a system, a systematic bottom-up approach is suggested, underpinned by failure behaviour models of components composed based on interaction models to create a system-level failure behaviour model. Interoperability and reusability of models are supported by a library of component failure models. The approach was illustrated with application to a case study of a steam boiler system. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer | |
dc.subject | Model-based reliability analysis | en_US |
dc.subject | Bayesian networks | en_US |
dc.subject | Reliability analysis | en_US |
dc.title | A Model-Based Reliability Analysis Method Using Bayesian Network | en_US |
dc.status.refereed | Yes | en_US |
dc.date.Accepted | 2021-09-10 | |
dc.date.application | 2021-11-01 | |
dc.type | Book chapter | en_US |
dc.date.EndofEmbargo | 2023-10-18 | |
dc.type.version | Accepted manuscript | en_US |
dc.description.publicnotes | The full text will be available at the end of the publisher's embargo: 18th Nov 2023 | |
dc.identifier.doi | https://doi.org/10.1007/978-3-030-87094-2_43 | |
dc.date.updated | 2021-12-10T17:31:27Z | |
refterms.dateFOA | 2021-12-22T16:32:17Z | |
dc.openaccess.status | Green Open Access | en_US |