Intelligent data analysis to calculate the operational reliability coefficient

Zoila Esther Morales Tabares; Alcides Cabrera Campos; Efrén Vázquez Silva; Roberto Antonio Infante Milanés

doi:10.1007/978-3-030-01132-1_8

Intelligent data analysis to calculate the operational reliability coefficient

Zoila Esther Morales Tabares, Alcides Cabrera Campos, Efrén Vázquez Silva, Roberto Antonio Infante Milanés

Grupo de Investigación en Nuevos Materiales y Procesos de Transformacion (GIMaT)

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

6 Citas (Scopus)

Resumen

Nowadays the complexity that medical equipment has reached means that not all failure patterns can be easily managed through maintenance activities, carried out after their manufacture and commissioning. For this reason, experts in electromedicine consider that the analysis of failure patterns should be carried out with the tools of reliability engineering, since medical equipment is a technology that is not without risks. Failures in these devices are caused by risks associated mainly with operator malfunctions, impairment of the electrical fluid that causes the stopping of procedures in execution in an unexpected manner and others inherent to the technology. All these risks lead to a dynamic working behaviour of medical equipment, which passes through a finite number of states: running, faulty and broken. As part of the analysis of failure patterns in medical equipment, the CONFEM algorithm is proposed in this manuscript to determine the operational reliability coefficient.

Idioma original	Inglés
Título de la publicación alojada	Progress in Artificial Intelligence and Pattern Recognition - 6th International Workshop, IWAIPR 2018, Proceedings
Editores	Yanio Hernández Heredia, Vladimir Milián Núñez, José Ruiz Shulcloper
Editorial	Springer Verlag
Páginas	68-76
Número de páginas	9
ISBN (versión impresa)	9783030011314
DOI	https://doi.org/10.1007/978-3-030-01132-1_8
Estado	Publicada - 1 ene. 2018
Evento	6th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2018 - Havana, Cuba Duración: 24 sep. 2018 → 26 sep. 2018

Serie de la publicación

Nombre	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen	11047 LNCS
ISSN (versión impresa)	0302-9743
ISSN (versión digital)	1611-3349

Conferencia

Conferencia	6th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2018
País/Territorio	Cuba
Ciudad	Havana
Período	24/09/18 → 26/09/18

Nota bibliográfica

Publisher Copyright:
© Springer Nature Switzerland AG 2018.

Acceder al documento

10.1007/978-3-030-01132-1_8

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http://www.scopus.com/inward/record.url?scp=85057258388&partnerID=8YFLogxK

Citar esto

Morales Tabares, Z. E., Cabrera Campos, A., Vázquez Silva, E., & Infante Milanés, R. A. (2018). Intelligent data analysis to calculate the operational reliability coefficient. En Y. H. Heredia, V. M. Núñez, & J. R. Shulcloper (Eds.), Progress in Artificial Intelligence and Pattern Recognition - 6th International Workshop, IWAIPR 2018, Proceedings (pp. 68-76). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11047 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-01132-1_8

Morales Tabares, Zoila Esther ; Cabrera Campos, Alcides ; Vázquez Silva, Efrén et al. / Intelligent data analysis to calculate the operational reliability coefficient. Progress in Artificial Intelligence and Pattern Recognition - 6th International Workshop, IWAIPR 2018, Proceedings. editor / Yanio Hernández Heredia ; Vladimir Milián Núñez ; José Ruiz Shulcloper. Springer Verlag, 2018. pp. 68-76 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Nowadays the complexity that medical equipment has reached means that not all failure patterns can be easily managed through maintenance activities, carried out after their manufacture and commissioning. For this reason, experts in electromedicine consider that the analysis of failure patterns should be carried out with the tools of reliability engineering, since medical equipment is a technology that is not without risks. Failures in these devices are caused by risks associated mainly with operator malfunctions, impairment of the electrical fluid that causes the stopping of procedures in execution in an unexpected manner and others inherent to the technology. All these risks lead to a dynamic working behaviour of medical equipment, which passes through a finite number of states: running, faulty and broken. As part of the analysis of failure patterns in medical equipment, the CONFEM algorithm is proposed in this manuscript to determine the operational reliability coefficient.",

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Morales Tabares, ZE, Cabrera Campos, A, Vázquez Silva, E & Infante Milanés, RA 2018, Intelligent data analysis to calculate the operational reliability coefficient. En YH Heredia, VM Núñez & JR Shulcloper (eds.), Progress in Artificial Intelligence and Pattern Recognition - 6th International Workshop, IWAIPR 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11047 LNCS, Springer Verlag, pp. 68-76, 6th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2018, Havana, Cuba, 24/09/18. https://doi.org/10.1007/978-3-030-01132-1_8

Intelligent data analysis to calculate the operational reliability coefficient. / Morales Tabares, Zoila Esther; Cabrera Campos, Alcides; Vázquez Silva, Efrén et al.
Progress in Artificial Intelligence and Pattern Recognition - 6th International Workshop, IWAIPR 2018, Proceedings. ed. / Yanio Hernández Heredia; Vladimir Milián Núñez; José Ruiz Shulcloper. Springer Verlag, 2018. p. 68-76 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11047 LNCS).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

TY - GEN

T1 - Intelligent data analysis to calculate the operational reliability coefficient

AU - Morales Tabares, Zoila Esther

AU - Cabrera Campos, Alcides

AU - Vázquez Silva, Efrén

AU - Infante Milanés, Roberto Antonio

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2018.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Nowadays the complexity that medical equipment has reached means that not all failure patterns can be easily managed through maintenance activities, carried out after their manufacture and commissioning. For this reason, experts in electromedicine consider that the analysis of failure patterns should be carried out with the tools of reliability engineering, since medical equipment is a technology that is not without risks. Failures in these devices are caused by risks associated mainly with operator malfunctions, impairment of the electrical fluid that causes the stopping of procedures in execution in an unexpected manner and others inherent to the technology. All these risks lead to a dynamic working behaviour of medical equipment, which passes through a finite number of states: running, faulty and broken. As part of the analysis of failure patterns in medical equipment, the CONFEM algorithm is proposed in this manuscript to determine the operational reliability coefficient.

AB - Nowadays the complexity that medical equipment has reached means that not all failure patterns can be easily managed through maintenance activities, carried out after their manufacture and commissioning. For this reason, experts in electromedicine consider that the analysis of failure patterns should be carried out with the tools of reliability engineering, since medical equipment is a technology that is not without risks. Failures in these devices are caused by risks associated mainly with operator malfunctions, impairment of the electrical fluid that causes the stopping of procedures in execution in an unexpected manner and others inherent to the technology. All these risks lead to a dynamic working behaviour of medical equipment, which passes through a finite number of states: running, faulty and broken. As part of the analysis of failure patterns in medical equipment, the CONFEM algorithm is proposed in this manuscript to determine the operational reliability coefficient.

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KW - Risks

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SN - 9783030011314

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Progress in Artificial Intelligence and Pattern Recognition - 6th International Workshop, IWAIPR 2018, Proceedings

A2 - Heredia, Yanio Hernández

A2 - Núñez, Vladimir Milián

A2 - Shulcloper, José Ruiz

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Y2 - 24 September 2018 through 26 September 2018

ER -

Morales Tabares ZE, Cabrera Campos A, Vázquez Silva E, Infante Milanés RA. Intelligent data analysis to calculate the operational reliability coefficient. En Heredia YH, Núñez VM, Shulcloper JR, editores, Progress in Artificial Intelligence and Pattern Recognition - 6th International Workshop, IWAIPR 2018, Proceedings. Springer Verlag. 2018. p. 68-76. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-01132-1_8

Intelligent data analysis to calculate the operational reliability coefficient

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