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Determination of the typical load profile of industry tasks using fuzzy C-Means

dc.contributor.authorBarreto, Rúben
dc.contributor.authorFaria, Pedro
dc.contributor.authorVale, Zita
dc.date.accessioned2021-03-04T17:43:11Z
dc.date.available2021-03-04T17:43:11Z
dc.date.issued2020
dc.description.abstractThis paper aims to promote the importance and advantages that the clustering method brings to the world of industry, making it possible to increase production efficiency and to manage the energy resources available better. The purpose of this paper is to group the consumption profiles of a task, in order to be able to determine which is the typical load profile of the task through the Fuzzy C-Means clustering method. The case study of this paper focuses on a task performed by three machines that make up a textile production line that makes several products. Each product, when going through a task performed by a specific machine, has a specific consumption and duration. Thus, by machine, it is determined which is the typical profile of ideal consumption to perform the designated task. In the same way, the general consumption profile of the task is highlighted, that is, the possible consumption profile to be expected when executing this task on one of the three machines.pt_PT
dc.description.sponsorshipThis work has received funding from Portugal 2020 under SPEAR project (NORTE-01-0247-FEDER-040224) and from FEDER Funds through COMPETE program and from National Funds through (FCT), Portugal under the project UIDB/00760/2020, and CEECIND/02887/2017.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.egyr.2020.11.094pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/17282
dc.language.isoengpt_PT
dc.publisherElsevierpt_PT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S2352484720315195?via%3Dihubpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectClusteringpt_PT
dc.subjectData miningpt_PT
dc.subjectFuzzy C-Meanspt_PT
dc.subjectTypical load profilept_PT
dc.subjectUnsupervised learningpt_PT
dc.titleDetermination of the typical load profile of industry tasks using fuzzy C-Meanspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage160pt_PT
oaire.citation.startPage155pt_PT
oaire.citation.titleEnergy Reportspt_PT
oaire.citation.volume6pt_PT
person.familyNameFaria
person.familyNameVale
person.givenNamePedro
person.givenNameZita
person.identifier632184
person.identifier.ciencia-idB212-2309-F9C3
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0002-5982-8342
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id7004115775
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication35e6a4ab-f644-4bc5-b6fc-9fd89c23d6c6
relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
relation.isAuthorOfPublication.latestForDiscovery35e6a4ab-f644-4bc5-b6fc-9fd89c23d6c6

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