Bibliographic citations
Espiritu, J., Huaynate, M. (2023). Modelo de gestión de mantenimiento para mejorar la disponibilidad de la maquinaria pesada de una empresa prestadora de servicios a minería usando RCM [Trabajo de Suficiencia Profesional, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/671831
Espiritu, J., Huaynate, M. Modelo de gestión de mantenimiento para mejorar la disponibilidad de la maquinaria pesada de una empresa prestadora de servicios a minería usando RCM [Trabajo de Suficiencia Profesional]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2023. http://hdl.handle.net/10757/671831
@misc{renati/413320,
title = "Modelo de gestión de mantenimiento para mejorar la disponibilidad de la maquinaria pesada de una empresa prestadora de servicios a minería usando RCM",
author = "Huaynate Ricaldi, Marco Anibal",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2023"
}
The objective of this study is to implement a maintenance management model to improve the availability of drilling machine in Pasco, Peru. This implementation is based on the principles of RCM and is based on an unbiased diagnosis that uses industrial engineering tools and techniques such as the Pareto diagram and the cause-effect diagram. The main objective under study is based on the drilling machine, model DD311 from the Sandvik brand, which currently has an availability of 78% and incurs an annual maintenance cost of $1,236,239. This problem identification led to the development of a solution based on the obtained hypothesis, pointing out interruptions in the lubrication system as a key problem that affects both the operation and the internal/external characteristics of the equipment. The proposed solution involves the use of engineering tools and techniques such as RCM as a model validated through scientific articles, which affirm its overall effectiveness. In conclusion, the RCM methodology proves to be a valid solution, as indicated by the statistical results, which show an increase in availability from 78% to 87%.
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