Ítem
Solo Metadatos

Using the Monte Carlo stochastic method to determine the optimal maintenance frequency of medical devices in real contexts

Mostrar el registro sencillo de la publicación
dc.creatorMiguel-Cruz A.spa
dc.creatorParra P.A.A.spa
dc.creatorOcampo A.F.C.spa
dc.creatorGuao V.S.P.spa
dc.creatorCorreal O. H.H.spa
dc.creatorHernández N.P.C.spa
dc.creatorCruz A.N.spa
dc.creatorRojas J.S.S.spa
dc.creatorTorres D.A.Q.spa
dc.creatorRodríguez-Dueñas, William R.spa
dc.date.accessioned2020-05-26T00:10:52Z
dc.date.available2020-05-26T00:10:52Z
dc.date.created2019spa
dc.description.abstractThe purpose of this study was to implement and validate a Monte Carlo Algorithm (MCA) to determine the best T value (the time between two preventative maintenances) that optimizes the achieved availability of equipment types. In doing so, we (1) collected 796 maintenance works orders from 16 medical devices installed in a 900-bed hospital; (2) we fitted the probability distributions for each of the inputs of the achieved availability mathematical model (the mean preventative and corrective service time (in hours)); (3) we generated a set of random inputs following a Weibull distribution of the achieved availability mathematical model; (4) we calculated the achieved availability for every random input generated; this process was repeated for “m” iterations (an accuracy of 1%, 95% CI, alpha = 0.05); (5) the trends of the mean achieved availability for the different maintenance T intervals versus mean time to failure (MTTF) for all the equipment types were plotted; finally, (6) the best T value with the maximum value of the achieved availability of a medical device type for a specific MTTF was the optimal target. The mean simulation time for all the cases was 12 min. The MCA was able to determine the best T value, optimizing the achieved availability in 81.25% of cases. In conclusion, the results showed that, on average, the T maintenance intervals determined by the MCA were statistically significantly different from the original T values suggested either by the clinical engineering department or third-party maintenance providers (MCATmean = 1.68 times/yr, ActualTmean = 2.56 times/yr, p = 0.008). © Springer Nature Singapore Pte Ltd. 2019.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1007/978-981-10-9023-3_49
dc.identifier.issn2006
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/24265
dc.language.isoengspa
dc.publisherSpringer Verlagspa
dc.relation.citationEndPage277
dc.relation.citationIssueNo. 3
dc.relation.citationStartPage273
dc.relation.citationTitleIFMBE Proceedings
dc.relation.citationVolumeVol. 68
dc.relation.ispartofIFMBE Proceedings, ISSN:2006, Vol.68, No.3 (2019); pp. 273-277spa
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85048303453&doi=10.1007%2f978-981-10-9023-3_49&partnerID=40&md5=1090092cc035df57e45457845ed4597cspa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)spa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocURspa
dc.subject.keywordBioinformaticsspa
dc.subject.keywordBiomedical engineeringspa
dc.subject.keywordBiomedical equipmentspa
dc.subject.keywordIntelligent systemsspa
dc.subject.keywordMaintenancespa
dc.subject.keywordStochastic systemsspa
dc.subject.keywordWeibull distributionspa
dc.subject.keywordAchieved availabilityspa
dc.subject.keywordClinical engineeringspa
dc.subject.keywordMaintenance intervalsspa
dc.subject.keywordMaintenance optimizationspa
dc.subject.keywordMonte carlo algorithmsspa
dc.subject.keywordMonte Carlo stochastic methodspa
dc.subject.keywordOptimal maintenance frequencyspa
dc.subject.keywordPreventative maintenancespa
dc.subject.keywordMonte Carlo methodsspa
dc.subject.keywordBiomedical engineeringspa
dc.subject.keywordClinical engineeringspa
dc.subject.keywordMaintenance optimizationspa
dc.subject.keywordMonte carlo simulationspa
dc.subject.keywordPreventative maintenance frequencyspa
dc.titleUsing the Monte Carlo stochastic method to determine the optimal maintenance frequency of medical devices in real contextsspa
dc.typeconferenceObjecteng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaDocumento de conferenciaspa
Archivos
Colecciones
Artículos