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Article . 2026
License: CC BY
Data sources: ZENODO
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Article . 2026
License: CC BY
Data sources: Datacite
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Article . 2026
License: CC BY
Data sources: Datacite
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Gemelos digitales en el mantenimiento predictivo

Authors: Aparicio Guevara, Melany Camila; Pinto Martínez, Leonardo Fabián; Quispe Vargas, Andree Styvens;

Gemelos digitales en el mantenimiento predictivo

Abstract

Este trabajo de investigación analiza el impacto de los gemelos digitales en el mantenimiento predictivo industrial. Los gemelos digitales son representaciones virtuales de activos físicos que, mediante el uso de sensores IoT, inteligencia artificial y análisis de datos en tiempo real, permiten monitorear el estado de la maquinaria, detectar anomalías y anticipar fallas antes de que ocurran. La investigación examina el funcionamiento de esta tecnología, sus principales ventajas frente a los métodos tradicionales de mantenimiento y las limitaciones que afectan su adopción, especialmente en el contexto industrial peruano. Asimismo, se revisan estudios recientes relacionados con la Industria 4.0, destacando el potencial de los gemelos digitales para mejorar la eficiencia operativa, reducir costos y aumentar la competitividad empresarial. Los resultados muestran que la integración de tecnologías como Internet de las Cosas (IoT), inteligencia artificial y Big Data permite optimizar la toma de decisiones y fortalecer las estrategias de mantenimiento predictivo, contribuyendo al desarrollo sostenible de los procesos industriales.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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