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Maintenance Plan Based on TPM for Turbine Recovery Machinery
dc.contributor.author | Lozada-Cepeda, José Antonio | |
dc.contributor.author | Lara-Calle, Rés | |
dc.contributor.author | Buele, Jorge | |
dc.date | 2021 | |
dc.date.accessioned | 2022-04-27T10:59:55Z | |
dc.date.available | 2022-04-27T10:59:55Z | |
dc.identifier.issn | 1742-6588 | |
dc.identifier.uri | https://reunir.unir.net/handle/123456789/12948 | |
dc.description.abstract | The maintenance and repair of the components of hydroelectric turbines require the use of specialized equipment. To keep these teams operational, it is proposed to design a master plan in order to develop a TPM philosophy for a vertical turning lathe. This project develops five of the twelve steps established by JIPM for the TPM implementation. This paper also provides the necessary documentation for 5S and autonomous maintenance applications. Also, some safety, health and environmental suggestions are provided. PM activities are chosen based on RCM techniques like CA and FMEA. And predictive maintenance activities are established following ISO 3655, 2006. All these activities including automotive maintenance ones are organized and scheduled. Finally, OEE rate is applied to the lathe to identify the principal losses on the machine. After applying this proposal there is an increase of 27.84% and 39.71% in availability and performance respectively. The OEE calculation has increased by 29.97%, thereby motivating readers to implement this methodology in other industries. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | IOP Publishing Ltd | es_ES |
dc.relation.ispartofseries | ;vol. 1878, nº 1 | |
dc.relation.uri | https://iopscience.iop.org/article/10.1088/1742-6596/1878/1/012034 | es_ES |
dc.rights | openAccess | es_ES |
dc.subject | hydroelectric power plants | es_ES |
dc.subject | lathes | es_ES |
dc.subject | Scopus(2) | es_ES |
dc.title | Maintenance Plan Based on TPM for Turbine Recovery Machinery | es_ES |
dc.type | article | es_ES |
reunir.tag | ~ARI | es_ES |
dc.identifier.doi | https://doi.org/10.1088/1742-6596/1878/1/012034 |
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