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Selection of the Method to Predict Vehicle Operation Reliability

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dc.contributor.author Makarova I.
dc.contributor.author Shubenkova K.
dc.contributor.author Mukhametdinov E.
dc.contributor.author Giniyatullin I.
dc.date.accessioned 2021-02-25T06:47:22Z
dc.date.available 2021-02-25T06:47:22Z
dc.date.issued 2020
dc.identifier.issn 2367-3370
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/161029
dc.description.abstract © Springer Nature Switzerland AG 2020. One of the main factors affecting the vehicles competitiveness is their reliability at every stage of the life cycle: design, production and operation. Vehicle’s technical health’s monitoring and diagnostics is very important during the operation stage, since this allows erasing causes of possible failures and predict vehicle’s life time. The paper authors in addition to the well-known FTA and FMEA, consider the logical-probabilistic method to predict vehicles’ operation reliability. To test hypotheses, authors have used the failures statistics received from the dealer-service network, and from the engine manufacturer’s reliability department. The authors proposed an intelligent system for predicting the vehicle engine operational reliability. The results of the study show that the use of the developed Intelligent system reduces the total failures number of crank mechanism elements and the engine as a whole. This means that possible failures can be predicted more accurately, as well as to ensure timely availability of necessary spare parts. At the same time, conditions must be created for the timely updating of initial data, its prompt processing and storage of ready-made solutions.
dc.relation.ispartofseries Lecture Notes in Networks and Systems
dc.subject Failure mode and effects analysis
dc.subject Failure prediction
dc.subject Fault tree analysis
dc.subject Logical-and-probabilistic method
dc.subject Operation reliability
dc.title Selection of the Method to Predict Vehicle Operation Reliability
dc.type Chapter
dc.relation.ispartofseries-volume 117
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 316
dc.source.id SCOPUS23673370-2020-117-SID85083987795


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  • Публикации сотрудников КФУ Scopus [24551]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

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