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dc.contributoren-US
dc.creatorCandanedo, Inés Sittón
dc.creatorGonzález, Sarah Rodríguez
dc.creatorMuñoz, Lilia
dc.creatorCandanedo, Inés Sittón
dc.creatorGonzález, Sarah Rodríguez
dc.creatorMuñoz, Lilia
dc.date2018-02-11
dc.date.accessioned2018-02-23T17:18:31Z
dc.date.available2018-02-23T17:18:31Z
dc.identifierhttps://knepublishing.com/index.php/KnE-Engineering/article/view/1458
dc.identifier10.18502/keg.v3i1.1458
dc.identifier.urihttp://ridda2.utp.ac.pa/handle/123456789/4373
dc.descriptionThe Internet of Things (IoT), the development and installation of advanced sensors for data collection, computer solutions for remote connection and other disruptive technologies are marking a transformation process in the industry; giving rise to what various sectors have called the fourth industrial revolution or Industry 4.0. With this process of change, organizations face both new opportunities and challenges. This article focuses on the modeling and integration of industrial data, generated by sensors installed in machines. The extraction of patterns is proposed, using data fusion techniques that allow the design of a predictive maintenance model. Finally, a case study is presented with a database that is applied to the Naive Bayes Algorithm to obtain predictions.Keywords: Industry 4.0, Sensors, Internet of Things, Pattern Extraction, Omnibus Models. en-US
dc.formatapplication/msword
dc.formatapplication/pdf
dc.formatapplication/xml
dc.languageeng
dc.publisherKnE Publishingen-US
dc.relationhttps://knepublishing.com/index.php/KnE-Engineering/article/view/1458/3268
dc.relationhttps://knepublishing.com/index.php/KnE-Engineering/article/view/1458/3519
dc.relationhttps://knepublishing.com/index.php/KnE-Engineering/article/view/1458/3520
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttps://creativecommons.org/licenses/by/4.0/
dc.source2518-6841
dc.sourceKnE Engineering; 6th Engineering, Science and Technology Conference - Panama 2017 (ESTEC 2017); 543-551en-US
dc.titleDiseño de un Modelo Predictivo en el Contexto Industria 4.0en-US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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