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

Papapanagiotou, Petros; Vaughan, James; Smola, Filip; Fleuriot, Jacques

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

dc.contributor.author	Papapanagiotou, Petros
dc.contributor.author	Vaughan, James
dc.contributor.author	Smola, Filip
dc.contributor.author	Fleuriot, Jacques
dc.date.accessioned	2020-12-24T19:10:55Z
dc.date.available	2020-12-24T19:10:55Z
dc.date.issued	2021-01-05
dc.description.abstract	We 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.extent	10 pages
dc.identifier.doi	10.24251/HICSS.2021.122
dc.identifier.isbn	978-0-9981331-4-0
dc.identifier.uri	http://hdl.handle.net/10125/70734
dc.language.iso	English
dc.relation.ispartof	Proceedings of the 54th Hawaii International Conference on System Sciences
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri	https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject	Case Studies of Artificial Intelligence, Business Intelligence, Analytics Technologies for Industry Platforms
dc.subject	analytics
dc.subject	formal methods
dc.subject	manufacturing
dc.subject	simulation
dc.subject	workflow
dc.title	A Real-world Case Study of Process and Data Driven Predictive Analytics for Manufacturing Workflows
prism.startingpage	1001

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