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dc.contributor.authorSarwar, Sajjad
dc.contributor.authorHaskins, Cecilia
dc.date.accessioned2022-03-28T10:31:04Z
dc.date.available2022-03-28T10:31:04Z
dc.date.created2022-03-18T13:39:49Z
dc.date.issued2021
dc.identifier.citationSarwar, S. & Haskins, C. (2021). Developing domain-specific AI-based tools to boost cross-enterprise knowledge reuse and improve quality. INCOSE International Symposium, 31(1), 343-371.en_US
dc.identifier.issn2334-5837
dc.identifier.urihttps://hdl.handle.net/11250/2987904
dc.description.abstractMHWirth observed that several quality issues surfaced during the product commissioning phase causing a negative impact on project cost, delivery time, and customer satisfaction. By using root cause analyses, this research found several links between poor quality and lack of proper knowledge management. With better knowledge management, most of these quality issues could be addressed and solved at an earlier stage of the product life cycle. Today different barriers are preventing organizations from taking full advantage of previously generated valuable knowledge. This paper explores how the use of Artificial Intelligence can boost knowledge reuse. The goal is to empower faster and more informed decision-making based on lessons learned in the past to minimize waste, rework, re-invention and redundancy.en_US
dc.language.isoengen_US
dc.relation.uri10.1002/j.2334-5837.2021.00842.x
dc.titleDeveloping domain-specific AI-based tools to boost cross-enterprise knowledge reuse and improve qualityen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2021 by Sajjad Sarwar and Cecilia Haskins. Permission granted to INCOSE to publish and use.en_US
dc.source.pagenumber343-371en_US
dc.source.volume31en_US
dc.source.journalINCOSE International Symposiumen_US
dc.source.issue1en_US
dc.identifier.doihttps://doi.org/10.1002/j.2334-5837.2021.00842.x
dc.identifier.cristin2010828
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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