Aplicación de escritorio para mantenimiento predictivo de equipos industriales de refrigeración a través de machine learning.

dc.contributorBarrera Gomez, Marien Rocio
dc.contributorAlfonso Diaz, Andres Leonardo
dc.contributorUniversidad Santo Tomas
dc.creatorQuiroga Niño, Jose Andres
dc.date.accessioned2023-07-13T14:53:40Z
dc.date.accessioned2023-09-06T13:16:28Z
dc.date.available2023-07-13T14:53:40Z
dc.date.available2023-09-06T13:16:28Z
dc.date.created2023-07-13T14:53:40Z
dc.date.issued2023-06-27
dc.identifierAlfonso Diaz, A. L., Barrera Gomez, M. R., & Quiroga Niño, J. A. (2023). Aplicacion de escritorio para mantenimiento predictivo de equipos industriales de refrigeración a través de machine learning. Universidad Santo Tomas.
dc.identifierhttp://hdl.handle.net/11634/51260
dc.identifierreponame:Repositorio Institucional Universidad Santo Tomás
dc.identifierinstname:Universidad Santo Tomás
dc.identifierrepourl:https://repository.usta.edu.co
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8679874
dc.description.abstractDevelopment of a platform that captures and analyzes information according to machine learning algorithms, from operational parameters and maintenance routines of industrial air conditioning systems. Predicting the occurrence of refrigerant gas leaks, by analyzing operational deviations.
dc.languagespa
dc.publisherUniversidad Santo Tomás
dc.publisherMaestría Ingeniería
dc.publisherFacultad de Ingeniería Electrónica
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dc.rightshttp://creativecommons.org/licenses/by-nc-nd/2.5/co/
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dc.rightsinfo:eu-repo/semantics/openAccess
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dc.rightsAtribución-NoComercial-SinDerivadas 2.5 Colombia
dc.titleAplicación de escritorio para mantenimiento predictivo de equipos industriales de refrigeración a través de machine learning.


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