<?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>0120-5609</journal-id>
<journal-title><![CDATA[Ingeniería e Investigación]]></journal-title>
<abbrev-journal-title><![CDATA[Ing. Investig.]]></abbrev-journal-title>
<issn>0120-5609</issn>
<publisher>
<publisher-name><![CDATA[Facultad de Ingeniería, Universidad Nacional de Colombia.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0120-56092018000200070</article-id>
<article-id pub-id-type="doi">10.15446/ing.investig.v38n2.65357</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Stochastic plans in SMEs: A novel multidimensional fuzzy logic system (mFLS) approach]]></article-title>
<article-title xml:lang="es"><![CDATA[Planes estocásticos en PyMEs: Novedoso enfoque de un sistema multidimensional difuso]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Baeza-Serrato]]></surname>
<given-names><![CDATA[Roberto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Guanajuato  ]]></institution>
<addr-line><![CDATA[Yuriria ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>08</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>08</month>
<year>2018</year>
</pub-date>
<volume>38</volume>
<numero>2</numero>
<fpage>70</fpage>
<lpage>78</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0120-56092018000200070&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0120-56092018000200070&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0120-56092018000200070&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT Manufacturing planning in small and medium enterprises (SMEs) uses a deterministic behavior, and the execution of these plans has a stochastic behavior. The evaluation of the manufacturing planning is based on a simple criterion as job on time or job delayed, without integrating conditions of uncertainty in the cycle times for each job. The aim of this paper is to propose a novel multidimensional stochastic Fuzzy Logic System (msFLS) approach to execute a plan with stochastic behavior in knitting SMEs and their evaluation. In this paper, two main contributions are identified. On one hand, the generation of a multi-dimensional diffuse system is proposed. Normal probability density function is used to generate multi linguistic variables to transform deterministic plans to stochastic plans in knitting SMEs. The fuzzy subsets or linguistic terms are labelled and categorized in a simple and clear language as poor (P), regular (R), good (G) and excellent (E). The Gaussian function was used as a membership function. On the other hand, the second contribution is the use of the sum of frequencies in the stage of implication for the multi-Fuzzy system. This research was validated through an integration of two different intelligent techniques such as the proposed novel msFLS and artificial neural networks. Neural networks were used as a generalization mechanism to perform any stochastic planning in the knitting companies. The inputs and outputs of the fuzzy system are used as training patterns in the neural network. The stages of the proposed approach are explicitly described and applied to random data and validated with real data of SMEs of the South of Guanajuato, Mexico. The proposed system had a positive response in the textile company, which continues to be used to carry out its manufacturing planning and the evaluation of its execution.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN La planeación de la manufactura en pequeñas y medianas empresas (PYMES) utiliza un comportamiento determinista, y la ejecución de estos planes tiene un comportamiento estocástico. La evaluación de la planeación de manufactura se basa en un criterio simple como trabajo a tiempo o trabajo retrasado, sin integrar condiciones de incertidumbre en los tiempos de ciclo para cada trabajo. En este artículo se propone un enfoque nuevo denominado sistema estocástico multidimensional de lógica difusa (msFLS) para realizar un plan con comportamiento estocástico en las pymes de tejido de punto. Esta investigación plantea dos contribuciones principales: La primera es la generación de un sistema difuso multidimensional. La función de densidad de probabilidad normal se utiliza para generar variables multi-lingüísticas como función de transformación del plan determinístico a un plan estocástico en las pymes de tejido de punto. Los subconjuntos difusos o los términos lingüísticos se etiquetan y categorizan en un claro y simple lenguaje como: pobres (P), regulares (R), buenos (G) y excelentes (E). La función gaussiana fue utilizada como función de membresía. El segundo es el uso del indicador "suma de frecuencias" en la etapa de implicación para el sistema multi-difuso. Esta investigación fue validada a través de la integración de dos técnicas inteligentes diferentes: msFLS y redes neuronales. Las redes neuronales se utilizaron como un mecanismo de generalización para realizar cualquier planeación estocástica en las empresas de tejido de punto. Las entradas y salidas del sistema difuso se utilizan como patrones de entrenamiento en la red neuronal. Las etapas del enfoque propuesto se describen explícitamente y se aplican a datos aleatorios múltiples y se validan con datos reales de PYMES del Sur de Guanajuato, México. El sistema propuesto tuvo una respuesta positiva en la empresa textil, el cual sigue utilizándose para realizar sus planeaciones de trabajos y la evaluación de su ejecución.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Stochastic plans]]></kwd>
<kwd lng="en"><![CDATA[fuzzy system]]></kwd>
<kwd lng="en"><![CDATA[normal probability density]]></kwd>
<kwd lng="en"><![CDATA[neural network]]></kwd>
<kwd lng="es"><![CDATA[Planes estocásticos]]></kwd>
<kwd lng="es"><![CDATA[Sistema difuso]]></kwd>
<kwd lng="es"><![CDATA[densidad de probabilidad normal]]></kwd>
<kwd lng="es"><![CDATA[red neuronal]]></kwd>
</kwd-group>
</article-meta>
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