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dc.contributor.authorNakhal, Antonio J.A.
dc.contributor.authorPatriarca, Riccardo
dc.contributor.authorDi Gravio, Giulio
dc.contributor.authorAntonioni, Giacomo
dc.contributor.authorPaltrinieri, Nicola
dc.date.accessioned2023-01-13T13:04:18Z
dc.date.available2023-01-13T13:04:18Z
dc.date.created2021-12-14T10:49:32Z
dc.date.issued2021
dc.identifier.citationChemical Engineering Transactions. 2021, 86 229-234.en_US
dc.identifier.issn1974-9791
dc.identifier.urihttps://hdl.handle.net/11250/3043398
dc.description.abstractReducing the frequency and severity of accidents in industrial processes is a continuous open challenge. Learning from previous events represents a crucial instrument to ensure an improved design of industrial plants, especially considering the complexity arising in everyday operations. This article is grounded on a database of industrial accidents involving hazardous substances and materials. The Major Hazard Incident Data Service (MHIDAS) was developed in 1986 by the Health and Safety Executive (HSE) to provide a reliable source of data on major hazard incidents and to learn for the past accidents. The database has more than 9000 accident reports covering the periods from 1950 to the end of the 1990s caused by hazardous substances/materials. This paper aims are to provide an understanding of MHIDAS data through quantitative analyses that can be obtained by exploiting the information collected through appropriate data management tools. Therefore, Information Technology (IT) services such as Business Intelligence (BI) tools have been used in this research. The paper describes the process of creating a BI model for data management on MHIDAS database to generate useful information on previous industrial safety events, allowing a detailed search engine as well through any event stored in MHIDAS.en_US
dc.language.isoengen_US
dc.publisherThe Italian Association of Chemical Engineeringen_US
dc.titleBusiness intelligence for the analysis of industrial accidents based on MHIDAS databaseen_US
dc.title.alternativeBusiness intelligence for the analysis of industrial accidents based on MHIDAS databaseen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber229-234en_US
dc.source.volume86en_US
dc.source.journalChemical Engineering Transactionsen_US
dc.identifier.doihttps://doi.org/10.3303/CET2186039
dc.identifier.cristin1968142
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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