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dc.contributor.authorLarrinaga, Felix
dc.contributor.otherKozma, Dániel
dc.contributor.otherVarga, Pal
dc.date.accessioned2019-10-31T09:13:55Z
dc.date.available2019-10-31T09:13:55Z
dc.date.issued2019
dc.identifier.isbn978-1-7281-0303-7en
dc.identifier.issn1946-0759en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=152146en
dc.identifier.urihttp://hdl.handle.net/20.500.11984/1485
dc.description.abstractWorkflow management is realised in manufacturing at the Enterprise- and Production (workstation) levels. The characteristics of business processes in these levels differ enough to prevent the adoption of a conventional modelling or implementation solution. The conceptualisation of an adequate and adaptable workflow management model that over-arches the heterogeneous business process levels is challenging. However,one of the encouragements of Industry 4.0 is to provide easy-to-use models and solutions that enable the effective implementation of production goals. The current paper addresses this challenge and – as a proof-of-concept – it demonstrates how the goals mentioned above can be achieved by combining the different manufacturing process models. To accomplish this, a workflow control engine needs to be designed and standardised respectively. Arrowhead is an IIoT(Industrial IoT) framework that dynamically and flexibly sup-ports automated manufacturing processes following Industry 4.0 expectations. This paper describes how its workflow management system, i.e., the Workflow Choreographer implements automated production. Furthermore, it details what the functions of this system are and how it applies and combines BPMN and CPN in practice to provide a solution for the given challenge.To verify its feasibility, the paper showcases a demo application of the concept as well.en
dc.description.sponsorshipUnión Europeaes
dc.description.sponsorshipGobierno Vascoes
dc.description.sponsorshipGobierno Vascoes
dc.language.isoengen
dc.publisherIEEEen
dc.rights© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.subjectDigital Productionen
dc.subjectColoured Petri Netsen
dc.subjectBPMNen
dc.subjectProductive 4.0en
dc.subjectIndustry 4.0en
dc.titleData-driven Workflow Management by utilising BPMN and CPN in IIoT Systems with the Arrowhead Frameworken
dc.typeinfo:eu-repo/semantics/conferenceObjecten
dcterms.accessRightsinfo:eu-repo/semantics/embargoedAccessen
dcterms.source2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). 10-13 September 2019, Zaragoza, Spain. IEEE, 2019en
dc.description.versioninfo:eu-repo/semantics/acceptedVersionen
local.contributor.groupIngeniería del software y sistemases
local.description.peerreviewedtrueen
local.description.publicationfirstpage385en
local.description.publicationlastpage392en
local.identifier.doihttp://dx.doi.org/10.1109/ETFA.2019.8869501en
local.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/737459/EU/Electronics and ICT as enabler for digital industry and optimized supply chain management covering the entire product lifecycle/PRODUCTIVE4.0en
local.relation.projectIDGV/Elkartek 2018/KK-2018-00104/Teknologia Ekin Hagin (T) Zerra Erabiliz/TEKINTZEen
local.relation.projectIDGV/Ikertalde Convocatoria 2019-2021/IT1326-19/CAPV//en
local.embargo.enddate2020-03-31
local.contributor.otherinstitutionBudapest University of Technology and Economicsen
local.source.detailsxxxeu_ES


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