A systematic review of multivariate uncertainty quantification for engineering systems

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dc.contributor.authorGrenyer, Alex
dc.contributor.authorErkoyuncu, John Ahmet
dc.contributor.authorZhao, Yifan
dc.contributor.authorRoy, Rajkumar
dc.date.accessioned2021-04-01T13:29:17Z
dc.date.available2021-04-01T13:29:17Z
dc.date.issued2021-03-31
dc.description.abstractEngineering systems must function effectively whilst maintaining reliability in service. Predicting maintenance costs and asset availability raises varying degrees of uncertainty from multiple sources. Previous reviews in this domain have assessed cost uncertainty and estimation for the entire life cycle. This paper presents a systematic review to investigate existing methodologies and challenges in uncertainty quantification, aggregation and forecasting for modern engineering systems through their in-service life. Approaches to forecast uncertainty here are hindered chiefly by data quality of available data, experience and knowledge. A total of 107 papers were analysed to answer three research questions based on the scope, through which two core research gaps were identified. An integrated combination of identified approaches will enhance rigour in uncertainty assessment and forecasting. This review contributes a systematic identification and assessment of current practices in uncertainty quantification and scientific methodologies to quantify, aggregate and forecast quantitative and qualitative uncertainties to better understand their impact on cost and availability to aid decision making throughout the in-service phase.en_UK
dc.identifier.citationGrenyer A, Erkoyuncu JA, Zhao Y, Roy R. (2021) A systematic review of multivariate uncertainty quantification for engineering systems. CIRP Journal of Manufacturing Science and Technology, Volume 33, May 2021, pp. 188-208en_UK
dc.identifier.issn1755-5817
dc.identifier.urihttps://doi.org/10.1016/j.cirpj.2021.03.004
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16540
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectAggregationen_UK
dc.subjectEngineering systemsen_UK
dc.subjectForecastingen_UK
dc.subjectMultivariateen_UK
dc.subjectUncertainty analysisen_UK
dc.subjectUncertainty quantificationen_UK
dc.titleA systematic review of multivariate uncertainty quantification for engineering systemsen_UK
dc.typeArticleen_UK

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