A Real-world Case Study of Process and Data Driven Predictive Analytics for Manufacturing Workflows

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dc.contributor.authorPapapanagiotou, Petros
dc.contributor.authorVaughan, James
dc.contributor.authorSmola, Filip
dc.contributor.authorFleuriot, Jacques
dc.date.accessioned2020-12-24T19:10:55Z
dc.date.available2020-12-24T19:10:55Z
dc.date.issued2021-01-05
dc.description.abstractWe present a novel application of business process modelling and simulation of manufacturing workflows. Using formal methods, we produce correct-by-construction executable models that can be simulated in an interleaved way. The simulation draws advanced analytics from live IoT monitoring as well as an ERP system to provide predictive business intelligence. We describe our process and resource modelling efforts in the context of a collaborative project with two manufacturing partners. We evaluate our results based on the improvement of the scheduling accuracy for real production flows.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2021.122
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/70734
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCase Studies of Artificial Intelligence, Business Intelligence, Analytics Technologies for Industry Platforms
dc.subjectanalytics
dc.subjectformal methods
dc.subjectmanufacturing
dc.subjectsimulation
dc.subjectworkflow
dc.titleA Real-world Case Study of Process and Data Driven Predictive Analytics for Manufacturing Workflows
prism.startingpage1001

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