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Evaluación de las solicitudes de mantenimiento correctivo usando técnicas de agrupamiento y reglas de asociación

In this research association discovering and clustering techniques for the resolution of the low efficiency problem in the sterilization service in a hospital under study were used. The aim was to find and to discriminate the main causes of the problem under study and then to apply corrective soluti...

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Bibliographic Details
Institution:Universidad EIA
Main Authors: Cruz, A. M. (Antonio Miguel), Barr, C. (Cameron), Castilla-Casado, N. (Norberto )
Format: Artículo de revista
Language:Español
Published: Biomédica, Mecatrónica y Mecánica 2014-04-23
Subjects:
RBI00033
TECNOLOGÍAS PARA LA SALUD
TECHNOLOGY IN HEALTH
DISINFECTION - ORGANIZATION AND ADMINISTRATION
DESINFECCIÓN - ORGANIZACIÓN Y ADMINISTRACIÓN
DESCUBRIMIENTO DE ASOCIACIONES
GESTIÓN TECNOLÓGICA
INGENIERÍA CLÍNICA
MINERÍA DE DATOS
TÉCNICAS DE AGRUPAMIENTOS
ASSOCIATION DISCOVERY
CLUSTERING TECHNIQUES
CLINICAL ENGINEERING
DATA MINING
TECHNOLOGY MANAGEMENT
Online Access:https://repository.eia.edu.co/handle/11190/445
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Summary:In this research association discovering and clustering techniques for the resolution of the low efficiency problem in the sterilization service in a hospital under study were used. The aim was to find and to discriminate the main causes of the problem under study and then to apply corrective solutions. To conduct this research the information contained in corrective maintenance work orders and service requests in the period under study (2002-2004) was collected. First a segmentation of the information was carried out using the indicator: corrective service request versus number of medical devices. The levels of the information segmentation were: equipment types, services or cost centre, original equipment manufacturer and models. Then the association discovery technique was used. It revealed that the main causes of low efficiency in sterilization service were: users’ training (errors in operation procedures), intrinsic failures in medical devices, and bad scheduled maintenance policies. Clustering technique uncovered the main causes of failures: malfunctioning of the power supply system (steam and water, in 75% of all cases). With the evidence obtained corrective actions were taken. The service requests dropped dramatically from 6.4 to 0.4 during the period 2005-2006.
Physical Description:12 p.
ISSN:ISSN 19099762