<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0379-3982</journal-id>
<journal-title><![CDATA[Revista Tecnología en Marcha]]></journal-title>
<abbrev-journal-title><![CDATA[Tecnología en Marcha]]></abbrev-journal-title>
<issn>0379-3982</issn>
<publisher>
<publisher-name><![CDATA[Instituto Tecnológico de Costa Rica]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0379-39822023000100042</article-id>
<article-id pub-id-type="doi">10.18845/tm.v36i1.5891</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Uso de regresión de soporte vectorial para el control de espuma metálica]]></article-title>
<article-title xml:lang=""><![CDATA[Using support vector regression for metal foam control]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Sanabria-Castro]]></surname>
<given-names><![CDATA[Alexis]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Meneses-Guzmán]]></surname>
<given-names><![CDATA[Marcela]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Chiné-Polito]]></surname>
<given-names><![CDATA[Bruno]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Instituto Tecnológico de Costa Rica  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Costa Rica</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Instituto Tecnológico de Costa Rica  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Costa Rica</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Instituto Tecnológico de Costa Rica  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Costa Rica</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2023</year>
</pub-date>
<volume>36</volume>
<numero>1</numero>
<fpage>42</fpage>
<lpage>53</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.sa.cr/scielo.php?script=sci_arttext&amp;pid=S0379-39822023000100042&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.sa.cr/scielo.php?script=sci_abstract&amp;pid=S0379-39822023000100042&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.sa.cr/scielo.php?script=sci_pdf&amp;pid=S0379-39822023000100042&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El monitoreo de perfiles se enfoca en aquellas variables de proceso o producto que son caracterizadas por una relación funcional de esta variable respecto del tiempo o el espacio. El objetivo de este trabajo es desarrollar una metodología basada en Regresión de Soporte Vectorial, SVR, para el monitoreo de perfiles no lineales, e implementarla a los perfiles de densidad de un material celular, espuma metálica de aluminio. La forma de un perfil en control está asociada a ciertas características mecánicas del producto, por lo que un cambio significativo de su forma seria detectado como un fuera de control por un método de monitoreo diseñado para este fin; si esto sucediera, se puede concluir que las propiedades mecánicas de la espuma son diferentes a las requeridas. La metodología considera el cálculo de curvas percentiles que serán la base para definir los límites de un gráfico de control, la estimación de parámetros del modelo de SVR con un Kernel Gausseano y con la ayuda de validación cruzada; se evalúa el desempeño del gráfico de control establecido apoyados en la técnica de boostrapping. El método propuesto es sencillo de interpretar y práctico. De acuerdo con los resultados, si la forma del perfil de densidad llegara a cambiar más allá de la indicada variabilidad natural del perfil, el método implementado lo detectaría como fuera de control con un error tipo I de 0.341% (ARLreal= 293).]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Profile monitoring focuses on the process or product variables that are characterized by a functional relationship of this variable with respect to time or space. The objective of this research is to develop a methodology based on Support Vector Regression, SVR, for no linear profiles monitoring and implement it to the density profiles of a cellular material, aluminum metal foam. The shape of a profile is associated to certain mechanic characteristics of a product which means that a significant change in the shape would be detected as an out-of-control observation by a monitoring method designed for this purpose; if this happened, it can be concluded that the mechanic properties would be different from those required. The methodology considers the estimation of percentile curves that will be the basis to define the control chart limits, and the estimation of the parameter Cost and Sigma of a SVR model with a Gaussian Kernel with the aid of cross-validation. The performance of the established control chart is evaluated supported by the boostrapping technique. The proposed method is practical and of simple interpretation. According to the results, if the shape of the density profile were to change beyond the shape indicated by the natural variability of the profile, the implemented method would detect it as out-of-control with a type I error of 0.341% (ARLreal = 293).]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Máquinas de soporte vectorial]]></kwd>
<kwd lng="es"><![CDATA[máquinas de soporte de regresión]]></kwd>
<kwd lng="es"><![CDATA[monitoreo de perfiles]]></kwd>
<kwd lng="es"><![CDATA[perfil de densidad]]></kwd>
<kwd lng="es"><![CDATA[espuma metálica]]></kwd>
<kwd lng="es"><![CDATA[control estadístico de procesos]]></kwd>
<kwd lng="en"><![CDATA[Support vector machines]]></kwd>
<kwd lng="en"><![CDATA[support regression machines]]></kwd>
<kwd lng="en"><![CDATA[profile monitoring]]></kwd>
<kwd lng="en"><![CDATA[density profile]]></kwd>
<kwd lng="en"><![CDATA[metal foam]]></kwd>
<kwd lng="en"><![CDATA[statistical process control]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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