<?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>0123-3033</journal-id>
<journal-title><![CDATA[Ingeniería y competitividad]]></journal-title>
<abbrev-journal-title><![CDATA[Ing. compet.]]></abbrev-journal-title>
<issn>0123-3033</issn>
<publisher>
<publisher-name><![CDATA[Facultad de Ingeniería, Universidad del Valle]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0123-30332022000200020</article-id>
<article-id pub-id-type="doi">10.25100/iyc.v24i2.11607</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Inferential statistics models to relate the rejections of an engine cold testing and the machining defects in camshaft assembly bores]]></article-title>
<article-title xml:lang="es"><![CDATA[Modelos estadísticos inferenciales para relacionar los rechazos de un banco de pruebas en frío y los defectos de maquinado en los barrenos de ensamble]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández-Nuñez]]></surname>
<given-names><![CDATA[Mario]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Bonilla-Blancas]]></surname>
<given-names><![CDATA[Angelica E.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Advanced Technology Center CIATEQ  ]]></institution>
<addr-line><![CDATA[Toluca ]]></addr-line>
<country>México</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2022</year>
</pub-date>
<volume>24</volume>
<numero>2</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0123-30332022000200020&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0123-30332022000200020&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0123-30332022000200020&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract In the manufacturing industry, it is important to reduce machining deviations as soon as possible to avoid the cost associated with reworks. The definition of mathematical models that predict future failures in the diagnosis of combustion engines associated with errors in machining is a way that helps to save time and money in a process. This paper proposes the analysis and establishment of correlations between the deviations of the machining in cylinder heads and the rejections of an engine cold testing in an automotive manufacturing company. To determine the relationships, a sample of heads and engines was measured in two months, and statistical models were established using inferential statistics. It was possible to establish 77 statistical models that allow predicting which machining of the cylinder heads are contributing to the rejects and therefore adjust the corresponding tools. Due to a large amount of data from the results of the 77 models, this article shows only one model which is one of the most representatives. Using this statistical model it was possible to know which characteristic of the tool should be adjusted in addition it was also possible to know that the test limits for oil pressure have to be adjusted in the engine cold testing.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En la industria manufacturera es de gran importancia reducir las desviaciones de maquinado tan pronto como sea posible para evitar costos asociados con los retrabajos. La definición de modelos matemáticos que predicen futuras fallas en el diagnóstico de motores de combustión asociados con los errores en los maquinados es una manera que ayuda a ahorrar tiempo y dinero en el proceso. Este trabajo propone el análisis y establecimiento de correlaciones entre las desviaciones del maquinado en cabezas de cilindros y los rechazos de un banco de pruebas en frio en una empresa que produce automóviles. Para determinar las relaciones, se midió una muestra de cabezas y motores en un período de dos meses y mediante estadística inferencial se establecieron modelos estadísticos. Se logró establecer 77 modelos estadísticos que permiten predecir qué maquinados de las cabezas de cilindros están contribuyendo a los rechazos y por tanto ajustar las herramientas correspondientes. Debido a la gran cantidad de datos de los resultados de los 77 modelos, este artículo muestra solo un modelo el cual es uno de los más representativos. Utilizando este modelo estadístico fue posible saber cuál característica de la herramienta debe ser ajustada además también se encontró que los límites de prueba para la presión de aceite tienen que ser ajustados en el banco de pruebas en frío.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Engine cold testing]]></kwd>
<kwd lng="en"><![CDATA[Head cylinder machining]]></kwd>
<kwd lng="en"><![CDATA[Inferential statistics]]></kwd>
<kwd lng="en"><![CDATA[Variables correlation]]></kwd>
<kwd lng="en"><![CDATA[Quality control]]></kwd>
<kwd lng="es"><![CDATA[Banco de pruebas en frío]]></kwd>
<kwd lng="es"><![CDATA[Maquinado de cabeza de cilindros]]></kwd>
<kwd lng="es"><![CDATA[Estadística inferencial]]></kwd>
<kwd lng="es"><![CDATA[Correlación de variables]]></kwd>
<kwd lng="es"><![CDATA[Control de calidad]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<label>1</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Qin]]></surname>
<given-names><![CDATA[SJ]]></given-names>
</name>
<name>
<surname><![CDATA[Dong]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[On data science for process systems modeling, control and operations]]></article-title>
<source><![CDATA[IFAC-PapersOnLine]]></source>
<year>2020</year>
<volume>53</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>11325-31</page-range></nlm-citation>
</ref>
<ref id="B2">
<label>2</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Melhem]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Ouladsine]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Pinaton]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Ananou]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Regression methods for predicting the product´s quality in the semiconductor manufacturing process]]></article-title>
<source><![CDATA[IFAC-PapersOnLine]]></source>
<year>2016</year>
<volume>49</volume>
<numero>12</numero>
<issue>12</issue>
<page-range>83-8</page-range></nlm-citation>
</ref>
<ref id="B3">
<label>3</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jia]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Xu]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Shen]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Fabric defect inspection based on lattice segmentation and template statistics]]></article-title>
<source><![CDATA[Information Sciences]]></source>
<year>2019</year>
<volume>512</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>964-84</page-range></nlm-citation>
</ref>
<ref id="B4">
<label>4</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Moica]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Radulescu]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Statistical controls have a significant influence on Non Quality Cost Cases study in a company those manufacturing aluminum casting components]]></article-title>
<source><![CDATA[Procedia Technology]]></source>
<year>2014</year>
<volume>12</volume>
<page-range>489-93</page-range></nlm-citation>
</ref>
<ref id="B5">
<label>5</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Machining error Control by integrating Multivariate Statistical]]></article-title>
<source><![CDATA[Chinese journal of aeronautics]]></source>
<year>2012</year>
<volume>25</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>937-47</page-range></nlm-citation>
</ref>
<ref id="B6">
<label>6</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Qi]]></surname>
<given-names><![CDATA[Q]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[T]]></given-names>
</name>
<name>
<surname><![CDATA[Scott]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Jiang]]></surname>
<given-names><![CDATA[X]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A correlational study of areal surface texture parameters on some typical machined surfaces]]></article-title>
<source><![CDATA[Procedia CIRP]]></source>
<year>2015</year>
<volume>27</volume>
<page-range>149-54</page-range></nlm-citation>
</ref>
<ref id="B7">
<label>7</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mahmoud Ali]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Mohamed Omran]]></surname>
<given-names><![CDATA[AN]]></given-names>
</name>
<name>
<surname><![CDATA[Mohamed]]></surname>
<given-names><![CDATA[Abd-El-Hakeem]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Prediction the correlations between hardness and tensile properties of aluminium silicon alloys produced by various modifiers and grain refineries using regression analysis and an artificial neural network model]]></article-title>
<source><![CDATA[Engineering Science and Technology, an International Journal]]></source>
<year>2021</year>
<volume>24</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>105-11</page-range></nlm-citation>
</ref>
<ref id="B8">
<label>8</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mikó]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Assessment of flatness error by regression analysis]]></article-title>
<source><![CDATA[Measurement]]></source>
<year>2021</year>
<volume>171</volume>
<page-range>108720</page-range></nlm-citation>
</ref>
<ref id="B9">
<label>9</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Heidarian]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Palkowski]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Predicting the eccentricity of tubes by developing a multiple regression model in tube drawing process with tilted die]]></article-title>
<source><![CDATA[Procedia manufacturing]]></source>
<year>2020</year>
<volume>50</volume>
<page-range>1-830</page-range></nlm-citation>
</ref>
<ref id="B10">
<label>10</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Fogaça]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Luiz de Souza]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Manéa]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Comparison between cold and hot test procedures in a company manufacturer of diesel engines]]></article-title>
<source><![CDATA[Gest Prod]]></source>
<year>2018</year>
<volume>25</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>343-53</page-range></nlm-citation>
</ref>
<ref id="B11">
<label>11</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Alvey]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Cerrato]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Application of]]></article-title>
<source><![CDATA[NVH techniques to engine production line test]]></source>
<year>2005</year>
<page-range>16-9</page-range></nlm-citation>
</ref>
<ref id="B12">
<label>12</label><nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[RAJAGOPAL]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<source><![CDATA[An Introduction to Cold Testing]]></source>
<year>2001</year>
<publisher-loc><![CDATA[USA ]]></publisher-loc>
</nlm-citation>
</ref>
<ref id="B13">
<label>13</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Martyr]]></surname>
<given-names><![CDATA[AJ]]></given-names>
</name>
<name>
<surname><![CDATA[Plint]]></surname>
<given-names><![CDATA[MA]]></given-names>
</name>
</person-group>
<source><![CDATA[Engine testing: The desing, building, modification and use powertrain test facilities]]></source>
<year>2012</year>
<edition>4</edition>
<publisher-loc><![CDATA[London ]]></publisher-loc>
<publisher-name><![CDATA[Butterworth-Heinemann]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B14">
<label>14</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Arasaratnam]]></surname>
<given-names><![CDATA[I]]></given-names>
</name>
<name>
<surname><![CDATA[Habibi]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Kelly]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Fountaine]]></surname>
<given-names><![CDATA[TJ]]></given-names>
</name>
<name>
<surname><![CDATA[Tjong]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<source><![CDATA[Engine fault detection using vibration signal reconstruction in the crank-angle domain]]></source>
<year>2011</year>
<publisher-name><![CDATA[SAE International]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B15">
<label>15</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Maul]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Mari]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Torres Irribarra]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Wilson]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The quality of measurement results in terms of the structural features of themeasurement process]]></article-title>
<source><![CDATA[Measurement]]></source>
<year>2018</year>
<volume>116</volume>
<page-range>611-20</page-range></nlm-citation>
</ref>
<ref id="B16">
<label>16</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Diamoutene]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Noureddine]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Kamsu-Foguem]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
<name>
<surname><![CDATA[Barro]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Quality control in machining using order statistics]]></article-title>
<source><![CDATA[Measurement]]></source>
<year>2017</year>
<volume>116</volume>
<page-range>596-601</page-range></nlm-citation>
</ref>
<ref id="B17">
<label>17</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Stief]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Baranowski]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Fault diagnosis using interpolated Kernel density estimate]]></article-title>
<source><![CDATA[Measurement]]></source>
<year>2021</year>
<volume>176</volume>
<page-range>109230</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
