<?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>0121-750X</journal-id>
<journal-title><![CDATA[Ingeniería]]></journal-title>
<abbrev-journal-title><![CDATA[ing.]]></abbrev-journal-title>
<issn>0121-750X</issn>
<publisher>
<publisher-name><![CDATA[Universidad Distrital Francisco José de Caldas]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0121-750X2024000200202</article-id>
<article-id pub-id-type="doi">10.14483/23448393.20895</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Scheduling in a Simple Assembly Robotics Cell to Minimize Earliness and Tardiness]]></article-title>
<article-title xml:lang="es"><![CDATA[Programación de trabajos en una celda robótica de ensamble simple para minimizar los adelantos y las tardanzas]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Muñoz-Guevara]]></surname>
<given-names><![CDATA[John Andrés]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Villegas-Florez]]></surname>
<given-names><![CDATA[Jairo Alberto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Jaramillo-Tabima]]></surname>
<given-names><![CDATA[Jhannier Jhoan]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Tecnológica de Pereira Facultad de Ciencias Empresariales ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Tecnológica de Pereira Facultad de Ciencias Empresariales ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Tecnológica de Pereira Facultad de Ciencias Empresariales ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>08</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>08</month>
<year>2024</year>
</pub-date>
<volume>29</volume>
<numero>2</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0121-750X2024000200202&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0121-750X2024000200202&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0121-750X2024000200202&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Background:  Robotics Assembly Cells (RAC) have been designed to meet the f lexibility requirements demanded by today&#8217;s globalized market. The objective is to manufacture a vast variety of products at a low cost, which requires equipment with a high level of flexibility, such as robots. The need to schedule a great variety of jobs in an RAC is a very relevant issue, as efficiency and productivity depend on the sequence in which jobs are scheduled. Studies around this matter have developed models with analytical and heuristic approaches, as well as simulation methods and genetic algorithms, seeking to improve performance measures based mainly on time, utilization, and costs.  Method:  The purpose of this article is to formulate an exact mathematical model using mixed-integer linear programming (MILP) to optimize small scheduling problems. The objective is to minimize the measure of performance related to the tardiness and earliness of jobs. This optimization aims to mitigate the effects of delays in product deliveries, queue times, and work-in-process inventory in subsequent processes. Doing so facilitates adherence to agreed-upon delivery deadlines and prevents bottlenecks in the assembly cell.  Results:  The proposed mathematical model generates optimal solutions to the job scheduling problem in the assembly cell, which serves as a case study. This addresses the need to minimize tardiness to meet delivery deadlines or minimize earliness while avoiding an increase in work-in-process inventories. The model ensures that optimal scheduling decisions are made to optimize both delivery performance and inventory levels.  Conclusions:  Due to the NP-hard complexity of the scheduling problem under study, the proposed mathematical model demonstrates computational efficiency in solving scheduling problems with fewer than 20 jobs. The model is designed to handle such smaller-scale problems within a reasonable computational time frame, considering the inherent complexity of the scheduling problem.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Contexto:  Las celdas robóticas de ensamble RAC han sido diseñadas para cumplir con los requerimientos de flexibilidad que exige el mercado globalizado actual. El objetivo es fabricar una alta variedad de productos a bajos costos, por lo cual se requiere de equipos con un alto nivel de f lexibilidad como los robots. La necesidad de programar una amplia variedad de trabajos en una RAC es un problema muy relevante, dado que la eficiencia y la productividad dependen de la secuencia en la cual se programan los trabajos. Los estudios alrededor de este asunto han desarrollado modelos con enfoques analíticos y heurísticos, así como métodos de simulación y algoritmos genéticos, que buscan mejorar medidas de desempeño basadas principalmente en el tiempo, el grado de utilización y el costo.  Método:  El propósito de este artículo es formular un modelo matemático exacto mediante programación lineal entera mixta (MILP) para optimizar problemas pequeños de programación. El objetivo es minimizar las medidas de desempeño de tardanza y adelanto de los trabajos. Esta optimización busca mitigar los efectos de las demoras en las entregas de los productos, los tiempos de cola y los inventarios de producto en proceso en instancias posteriores. Esto permite cumplir con los plazos de entrega pactados y evita bloqueos en la celda de ensamble.  Resultados:  El modelo matemático propuesto genera soluciones óptimas al problema de programación de trabajos en la celda de ensamble propuesta, lo que sirve como caso de estudio. Esto aborda la necesidad de minimizar las tardanzas para cumplir con los plazos de entrega o de minimizar los adelantos y evitar un aumento en los inventarios de producto en proceso. El modelo garantiza que se tomen decisiones óptimas de programación tanto para mejorar los tiempos de entrega como los niveles de inventario.  Conclusiones:  Debido a la complejidad NP-difícil del problema de programación estudiado, el modelo matemático propuesto demuestra eficiencia computacional en la resolución de problemas de programación con menos de 20 trabajos. El modelo está diseñado para manejar tales problemas de menor escala dentro de un marco de tiempo computacional razonable, considerando la complejidad inherente del problema de programación.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[robotic assembly cell]]></kwd>
<kwd lng="en"><![CDATA[tardiness]]></kwd>
<kwd lng="en"><![CDATA[scheduling]]></kwd>
<kwd lng="es"><![CDATA[celdas de ensamble robóticas]]></kwd>
<kwd lng="es"><![CDATA[tardanza]]></kwd>
<kwd lng="es"><![CDATA[programación.]]></kwd>
</kwd-group>
</article-meta>
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<given-names><![CDATA[W]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Single-machine due-date assignment scheduling with generalized earliness-tardiness penalties including proportional setup times]]></article-title>
<source><![CDATA[J. Appl. Math. Comput.]]></source>
<year>2022</year>
<volume>68</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>1013-31</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
