A Data Integration Framework for Additive Manufacturing Big Data Management

dc.creatorPerišić, Milica
dc.creatorMilenković, Dimitrije
dc.creatorLu, Yan
dc.creatorJones, Albert
dc.creatorIvezić, Nenad
dc.creatorKulvatunyou, Boonserm
dc.date.accessioned2021-12-07T17:59:01Z
dc.date.available2021-12-07T17:59:01Z
dc.date.issued2021
dc.description.abstractLarge amounts of data are generated throughout the entire, AM, part-development lifecycle. Data are generated by various functions within process monitoring, material characterization, equipment status, and part qualification. Hence, data integration and management are critical in streamlining, accelerating, certifying, and deploying these functions. However, achieving that integration and management has several challenges because AM data embodies the four characteristics of Big Data - volume, velocity, variety, and veracity. This paper proposes an AM framework as a foundation for addressing those challenges. In the framework, AM data are streamed, curated, and configured automatically for real-time analysis and batch processing, which increases the effectiveness of archiving and querying that data. The framework also includes a description of the associated AM metadata, which links the various data types and improves browsing, discovering, and analyzing that data. Finally, the framework can be used to derive requirements for standards that enable data sharing.en_US
dc.description.departmentMechanical Engineeringen_US
dc.identifier.urihttps://hdl.handle.net/2152/90738
dc.identifier.urihttp://dx.doi.org/10.26153/tsw/17657
dc.language.isoengen_US
dc.publisherUniversity of Texas at Austinen_US
dc.relation.ispartof2021 International Solid Freeform Fabrication Symposiumen_US
dc.rights.restrictionOpenen_US
dc.subjectdata integration frameworken_US
dc.subjectdata integrationen_US
dc.subjectdata managementen_US
dc.subjectadditive manufacturingen_US
dc.titleA Data Integration Framework for Additive Manufacturing Big Data Managementen_US
dc.typeConference paperen_US

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