Clustering Techniques
This paper investigates the use of clustering technique to characterize the providers of maintenance services in a health-care institution according to their performance. A characterization of the inventory of equipment from seven pilot areas was carried out first (including 264 medical devices). Th...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2010
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/26428
- Acceso en línea:
- https://doi.org/10.1109/memb.2009.935708
https://repository.urosario.edu.co/handle/10336/26428
- Palabra clave:
- Cluster Analysis
Contract Services
Data Interpretation
Statistical
Internationality
Maintenance
- Rights
- License
- Restringido (Acceso a grupos específicos)
id |
EDOCUR2_a3b23bafb4cdc362b94fc90c3cd5cd7a |
---|---|
oai_identifier_str |
oai:repository.urosario.edu.co:10336/26428 |
network_acronym_str |
EDOCUR2 |
network_name_str |
Repositorio EdocUR - U. Rosario |
repository_id_str |
|
spelling |
f2e876d6-94d1-4fd7-bc85-4194ad0925a6-13c95cdb3-32f4-44a5-ad4e-f55d353553f1-1b07b6dc8-d900-419c-9938-e67c3c1589fd-12020-08-06T16:21:41Z2020-08-06T16:21:41Z2010-03This paper investigates the use of clustering technique to characterize the providers of maintenance services in a health-care institution according to their performance. A characterization of the inventory of equipment from seven pilot areas was carried out first (including 264 medical devices). The characterization study concluded that the inventory on a whole is old [exploitation time (ET)/useful life (UL) average is 0.78] and has high maintenance service costs relative to the original cost of acquisition (service cost /acquisition cost average 8.61%). A monitoring of the performance of maintenance service providers was then conducted. The variables monitored were response time (RT), service time (ST), availability, and turnaround time (TAT). Finally, the study grouped maintenance service providers into clusters according to performance. The study grouped maintenance service providers into the following clusters. Cluster 0: Identified with the best performance, the lowest values of TAT, RT, and ST, with an average TAT value of 1.46 days; Clusters 1 and 2: Identified with the poorest performance, highest values of TAT, RT, and ST, and an average TAT value of 9.79 days; and Cluster 3: Identified by medium-quality performance, intermediate values of TAT, RT, and ST, and an average TAT value of 2.56 daysapplication/pdfhttps://doi.org/10.1109/memb.2009.935708ISSN: 2154-2287EISSN: 2154-2317https://repository.urosario.edu.co/handle/10336/26428engJournal & Magazines126No. 2119IEEE PulseVol. 29IEEE Pulse, ISSN: 2154-2287 ; EISSN: 2154-2317, Vol.29, No.2 (2010-03); pp.119-126https://ieeexplore.ieee.org/document/5431943/authors#authorsRestringido (Acceso a grupos específicos)http://purl.org/coar/access_right/c_16ecIEEE Pulseinstname:Universidad del Rosarioreponame:Repositorio Institucional EdocURCluster AnalysisContract ServicesData InterpretationStatisticalInternationalityMaintenanceClustering TechniquesTécnicas de agrupamientoarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Cruz, Antonio MiguelUsaquén Perilla, Sandra PatriciaVanegas Pabón, Nidia Nelly10336/26428oai:repository.urosario.edu.co:10336/264282022-05-02 07:37:15.345176https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co |
dc.title.spa.fl_str_mv |
Clustering Techniques |
dc.title.TranslatedTitle.spa.fl_str_mv |
Técnicas de agrupamiento |
title |
Clustering Techniques |
spellingShingle |
Clustering Techniques Cluster Analysis Contract Services Data Interpretation Statistical Internationality Maintenance |
title_short |
Clustering Techniques |
title_full |
Clustering Techniques |
title_fullStr |
Clustering Techniques |
title_full_unstemmed |
Clustering Techniques |
title_sort |
Clustering Techniques |
dc.subject.keyword.spa.fl_str_mv |
Cluster Analysis Contract Services Data Interpretation Statistical Internationality Maintenance |
topic |
Cluster Analysis Contract Services Data Interpretation Statistical Internationality Maintenance |
description |
This paper investigates the use of clustering technique to characterize the providers of maintenance services in a health-care institution according to their performance. A characterization of the inventory of equipment from seven pilot areas was carried out first (including 264 medical devices). The characterization study concluded that the inventory on a whole is old [exploitation time (ET)/useful life (UL) average is 0.78] and has high maintenance service costs relative to the original cost of acquisition (service cost /acquisition cost average 8.61%). A monitoring of the performance of maintenance service providers was then conducted. The variables monitored were response time (RT), service time (ST), availability, and turnaround time (TAT). Finally, the study grouped maintenance service providers into clusters according to performance. The study grouped maintenance service providers into the following clusters. Cluster 0: Identified with the best performance, the lowest values of TAT, RT, and ST, with an average TAT value of 1.46 days; Clusters 1 and 2: Identified with the poorest performance, highest values of TAT, RT, and ST, and an average TAT value of 9.79 days; and Cluster 3: Identified by medium-quality performance, intermediate values of TAT, RT, and ST, and an average TAT value of 2.56 days |
publishDate |
2010 |
dc.date.created.spa.fl_str_mv |
2010-03 |
dc.date.accessioned.none.fl_str_mv |
2020-08-06T16:21:41Z |
dc.date.available.none.fl_str_mv |
2020-08-06T16:21:41Z |
dc.type.eng.fl_str_mv |
article |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.spa.spa.fl_str_mv |
Artículo |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1109/memb.2009.935708 |
dc.identifier.issn.none.fl_str_mv |
ISSN: 2154-2287 EISSN: 2154-2317 |
dc.identifier.uri.none.fl_str_mv |
https://repository.urosario.edu.co/handle/10336/26428 |
url |
https://doi.org/10.1109/memb.2009.935708 https://repository.urosario.edu.co/handle/10336/26428 |
identifier_str_mv |
ISSN: 2154-2287 EISSN: 2154-2317 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.citationEndPage.none.fl_str_mv |
126 |
dc.relation.citationIssue.none.fl_str_mv |
No. 2 |
dc.relation.citationStartPage.none.fl_str_mv |
119 |
dc.relation.citationTitle.none.fl_str_mv |
IEEE Pulse |
dc.relation.citationVolume.none.fl_str_mv |
Vol. 29 |
dc.relation.ispartof.spa.fl_str_mv |
IEEE Pulse, ISSN: 2154-2287 ; EISSN: 2154-2317, Vol.29, No.2 (2010-03); pp.119-126 |
dc.relation.uri.spa.fl_str_mv |
https://ieeexplore.ieee.org/document/5431943/authors#authors |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_16ec |
dc.rights.acceso.spa.fl_str_mv |
Restringido (Acceso a grupos específicos) |
rights_invalid_str_mv |
Restringido (Acceso a grupos específicos) http://purl.org/coar/access_right/c_16ec |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
Journal & Magazines |
dc.source.spa.fl_str_mv |
IEEE Pulse |
institution |
Universidad del Rosario |
dc.source.instname.none.fl_str_mv |
instname:Universidad del Rosario |
dc.source.reponame.none.fl_str_mv |
reponame:Repositorio Institucional EdocUR |
repository.name.fl_str_mv |
Repositorio institucional EdocUR |
repository.mail.fl_str_mv |
edocur@urosario.edu.co |
_version_ |
1814167722014015488 |