Statistical analysis of surface roughness of machined graphite by means of CNC milling
The aim of this research is to analyze the influence of cutting speed, feed rate and cutting depth on the surface finish of grade GSP-70 graphite specimens for use in electrical discharge machining (EDM) for material removal by means of Computer Numerical Control (CNC) milling with low-speed machini...
- Autores:
-
Sánchez López, Orquídea
Rosas González, Armando
Hernández Castillo, Ignacio
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2016
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/67596
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/67596
http://bdigital.unal.edu.co/68625/
- Palabra clave:
- 62 Ingeniería y operaciones afines / Engineering
Graphite
factorial design
average roughness
percentage of predictive error
Grafito
diseño factorial
rugosidad media
porcentaje del error predictivo
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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| dc.title.spa.fl_str_mv |
Statistical analysis of surface roughness of machined graphite by means of CNC milling |
| title |
Statistical analysis of surface roughness of machined graphite by means of CNC milling |
| spellingShingle |
Statistical analysis of surface roughness of machined graphite by means of CNC milling 62 Ingeniería y operaciones afines / Engineering Graphite factorial design average roughness percentage of predictive error Grafito diseño factorial rugosidad media porcentaje del error predictivo |
| title_short |
Statistical analysis of surface roughness of machined graphite by means of CNC milling |
| title_full |
Statistical analysis of surface roughness of machined graphite by means of CNC milling |
| title_fullStr |
Statistical analysis of surface roughness of machined graphite by means of CNC milling |
| title_full_unstemmed |
Statistical analysis of surface roughness of machined graphite by means of CNC milling |
| title_sort |
Statistical analysis of surface roughness of machined graphite by means of CNC milling |
| dc.creator.fl_str_mv |
Sánchez López, Orquídea Rosas González, Armando Hernández Castillo, Ignacio |
| dc.contributor.author.spa.fl_str_mv |
Sánchez López, Orquídea Rosas González, Armando Hernández Castillo, Ignacio |
| dc.subject.ddc.spa.fl_str_mv |
62 Ingeniería y operaciones afines / Engineering |
| topic |
62 Ingeniería y operaciones afines / Engineering Graphite factorial design average roughness percentage of predictive error Grafito diseño factorial rugosidad media porcentaje del error predictivo |
| dc.subject.proposal.spa.fl_str_mv |
Graphite factorial design average roughness percentage of predictive error Grafito diseño factorial rugosidad media porcentaje del error predictivo |
| description |
The aim of this research is to analyze the influence of cutting speed, feed rate and cutting depth on the surface finish of grade GSP-70 graphite specimens for use in electrical discharge machining (EDM) for material removal by means of Computer Numerical Control (CNC) milling with low-speed machining (LSM). A two-level factorial design for each of the three established factors was used for the statistical analysis. The analysis of variance (ANOVA) indicates that cutting speed and feed rate are the two most significant factors with regard to the roughness obtained with grade GSP-70 graphite by means of CNC milling. A second order regression analysis was also conducted to estimate the roughness average (Ra) in terms of the cutting speed, feed rate and cutting depth. Finally, the comparison between predicted roughness by means of a second order regression model and the roughness obtained by machined specimens considering the combinations of low and high levels of roughness is also presented. |
| publishDate |
2016 |
| dc.date.issued.spa.fl_str_mv |
2016-09-01 |
| dc.date.accessioned.spa.fl_str_mv |
2019-07-03T04:38:08Z |
| dc.date.available.spa.fl_str_mv |
2019-07-03T04:38:08Z |
| dc.type.spa.fl_str_mv |
Artículo de revista |
| dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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http://purl.org/coar/resource_type/c_6501 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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Text |
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http://purl.org/redcol/resource_type/ART |
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http://purl.org/coar/resource_type/c_6501 |
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publishedVersion |
| dc.identifier.issn.spa.fl_str_mv |
ISSN: 2248-8723 |
| dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/67596 |
| dc.identifier.eprints.spa.fl_str_mv |
http://bdigital.unal.edu.co/68625/ |
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ISSN: 2248-8723 |
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https://repositorio.unal.edu.co/handle/unal/67596 http://bdigital.unal.edu.co/68625/ |
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spa |
| language |
spa |
| dc.relation.spa.fl_str_mv |
https://revistas.unal.edu.co/index.php/ingeinv/article/view/53603 |
| dc.relation.ispartof.spa.fl_str_mv |
Universidad Nacional de Colombia Revistas electrónicas UN Ingeniería e Investigación Ingeniería e Investigación |
| dc.relation.references.spa.fl_str_mv |
Sánchez López, Orquídea and Rosas González, Armando and Hernández Castillo, Ignacio (2016) Statistical analysis of surface roughness of machined graphite by means of CNC milling. Ingeniería e Investigación, 36 (3). pp. 89-94. ISSN 2248-8723 |
| dc.rights.spa.fl_str_mv |
Derechos reservados - Universidad Nacional de Colombia |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
| dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
| dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0/ |
| dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
Atribución-NoComercial 4.0 Internacional Derechos reservados - Universidad Nacional de Colombia http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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application/pdf |
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Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ingeniería |
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Universidad Nacional de Colombia |
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Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Sánchez López, Orquídeab93e1a60-f8ca-4963-849a-b2e732dd7f9e300Rosas González, Armando30d2f32a-714d-4f51-93c4-e9eb0aed5550300Hernández Castillo, Ignacio8b26e697-c6fa-43bf-9444-1fdd8bb9026a3002019-07-03T04:38:08Z2019-07-03T04:38:08Z2016-09-01ISSN: 2248-8723https://repositorio.unal.edu.co/handle/unal/67596http://bdigital.unal.edu.co/68625/The aim of this research is to analyze the influence of cutting speed, feed rate and cutting depth on the surface finish of grade GSP-70 graphite specimens for use in electrical discharge machining (EDM) for material removal by means of Computer Numerical Control (CNC) milling with low-speed machining (LSM). A two-level factorial design for each of the three established factors was used for the statistical analysis. The analysis of variance (ANOVA) indicates that cutting speed and feed rate are the two most significant factors with regard to the roughness obtained with grade GSP-70 graphite by means of CNC milling. A second order regression analysis was also conducted to estimate the roughness average (Ra) in terms of the cutting speed, feed rate and cutting depth. Finally, the comparison between predicted roughness by means of a second order regression model and the roughness obtained by machined specimens considering the combinations of low and high levels of roughness is also presented.El objetivo de esta investigación es analizar la influencia de la velocidad de corte, la velocidad de avance y la profundidad de corte en el acabado superficial de probetas de grafito grado GSP-70, para su uso en la remoción de material mediante descarga eléctrica (EDM), generadas mediante el proceso de fresado de control numérico computarizado (CNC) con velocidades bajas de maquinado (LSM). Para el análisis estadístico, se utilizó un diseño factorial con dos niveles en cada uno de los tres factores establecidos. Del análisis de varianza (ANOVA) calculado, se obtuvo que la velocidad de corte y la velocidad de avance son los factores más significativos en la rugosidad obtenida en el grafito grado GSP-70 usando fresado CNC. Así mismo, se realizó un análisis de regresión de un modelo de segundo orden para estimar la rugosidad media (Ra) en términos de la velocidad de corte, velocidad de avance y profundidad de corte. Por último, se presenta la comparación entre la rugosidad estimada mediante el modelo de regresión de segundo orden y la rugosidad obtenida de las probetas maquinadas considerando las combinaciones de menor y mayor rugosidad.application/pdfspaUniversidad Nacional de Colombia - Sede Bogotá - Facultad de Ingenieríahttps://revistas.unal.edu.co/index.php/ingeinv/article/view/53603Universidad Nacional de Colombia Revistas electrónicas UN Ingeniería e InvestigaciónIngeniería e InvestigaciónSánchez López, Orquídea and Rosas González, Armando and Hernández Castillo, Ignacio (2016) Statistical analysis of surface roughness of machined graphite by means of CNC milling. Ingeniería e Investigación, 36 (3). pp. 89-94. ISSN 2248-872362 Ingeniería y operaciones afines / EngineeringGraphitefactorial designaverage roughnesspercentage of predictive errorGrafitodiseño factorialrugosidad mediaporcentaje del error predictivoStatistical analysis of surface roughness of machined graphite by means of CNC millingArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL53603-313292-1-PB.pdfapplication/pdf1175023https://repositorio.unal.edu.co/bitstream/unal/67596/1/53603-313292-1-PB.pdf5f7ae258310c066c90902c0590870e84MD51THUMBNAIL53603-313292-1-PB.pdf.jpg53603-313292-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg8438https://repositorio.unal.edu.co/bitstream/unal/67596/2/53603-313292-1-PB.pdf.jpg314e6d90445a535318beb9b02a66471eMD52unal/67596oai:repositorio.unal.edu.co:unal/675962024-05-22 23:33:53.303Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |