Diseño de un Modelo Predictivo en el Contexto Industria 4.0

 

Authors
Candanedo, Inés Sittón; González, Sarah Rodríguez; Muñoz, Lilia
Format
Article
Status
publishedVersion
Description

The 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. 

Publication Year
2018
Language
eng
Topic
Repository
RI de Documento Digitales de Acceso Abierto de la UTP
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https://knepublishing.com/index.php/KnE-Engineering/article/view/1458
http://ridda2.utp.ac.pa/handle/123456789/4373
Rights
openAccess
License
https://creativecommons.org/licenses/by/4.0/