dc.contributorAvendaño Prieto, Gerardo
dc.contributorhttps://orcid.org/0000-0003-2675-3548
dc.contributorhttps://scholar.google.com/citations?user=8bxQF5cAAAAJ&hl=es
dc.contributorhttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000309699
dc.creatorCorredor Pinilla, Cristian David
dc.date.accessioned2022-01-27T14:09:49Z
dc.date.available2022-01-27T14:09:49Z
dc.date.created2022-01-27T14:09:49Z
dc.date.issued2022-01-20
dc.identifierCorredor Pinilla, C. D. (2022). Diseño de una propuesta de mejoramiento de la planeación agregada de una empresa del sector lácteo mediante un modelo de programación lineal. [Trabajo de pregrado, Universidad Santo Tomás]. Repositorio institucional.
dc.identifierhttp://hdl.handle.net/11634/42687
dc.identifierreponame:Repositorio Institucional Universidad Santo Tomás
dc.identifierinstname:Universidad Santo Tomás
dc.identifierrepourl:https://repository.usta.edu.co
dc.description.abstractThe dairy industry faces a competitive environment, this has led to producers facing a logical restructuring in their operations, pressuring them to improve their production planning to meet the dynamics of demand in the market, the relentless emergence of new players in the market leads companies to create intelligence units to know the markets, so that the way in which their processes are carried out must evolve in such a way as to make the most of resources, normally, the production plan and manufacturing is guided by marketing planning, the production plan determines how to use and allocate resources efficiently, that is why companies have to develop strategies that are framed with what consumers live and with the reality that surrounds them, and one of these strategies is to find the best way to do things internally, planning and scheduling the means needed to manufacture, using human resources, technological systems, machines that strategically enable the achievement of managerial goals. (Yaghin, 2020) Information technology in industry has become a competitive strategy that supports business processes by providing interconnection and globalization, both altering the rules of competition, Therefore, it is a determining factor as strategic and operational support supporting immediate decisions and adaptations of disruptive markets. That is why a new challenge is presented in which we must rethink the way things have been done, in other words, analyze and modify the process of planning and programming of production, making it more optimal, so day by day to become more competitive. (Hernandez, Lora Freyre, Moreno Garcia, Parra Perez, & Fajardo Alcolea, 2017) The present research designs the aggregate production plan in a dairy industry by performing linear programming models based on resource constraints that restrict the model, in order to solve the problem of overproduction that the company has. The case study is the company Villa del Queso dedicated to the production of dairy products research will be carried out in the environment as the production chain has been developing in order to present a proposal for improvement in its production plan. In order to design the production plan, a diagnosis of the situation will be made, analysing how its production processes and productive activities are carried out, since they have generated a surplus of output, bearing in mind that it already has a structured plan that does not meet management targets, the forecast of the time series best suited to the production capacity and demand of its historical sales will then be determined, the production plan shall then be established taking into account the historical information of the production periods, then determine the inventory capacity that the company can have with the compression of the above linear programming models are used with the goal of minimizing costs under the limitations of the organization. In accordance with this it is sought to understand which is the production process more suited to the production of dairy products and also established which model best responds to fluctuations in demand therefore in this research mathematical formulismos will be used will be optimized with a high-level tool such as the General Algebraic Modeling System software.
dc.languagespa
dc.publisherUniversidad Santo Tomás
dc.publisherPregrado Ingeniería Industrial
dc.publisherFacultad de Ingeniería Industrial
dc.relationRamírez Torres, N., & Sánchez Pineda , D. (06 de 07 de 2017). Diseño de un modelo de programación lineal para la planeación de producción en un cultivo de fresa, según factores costo/beneficio y capacidades productivas en un periodo temporal definido. Bogotá, Colombia.
dc.relationArbós, L. C. (2012). Planificación de la producción. Gestión de materiales: Organización de la producción y dirección de operaciones. Madrid: Ediciones Diaz de Santos.
dc.relationAtziry, C. (2016). Analysis of time-series on the forecast of the demand of storage of perishable productsAnálise de séries temporais na previsão da procura para o armazenamento de mercadorias perecíveis. Estudios Gerenciales, Icesi.
dc.relationBarbosa Correa, R., & Llinás Solano, H. (2016). Procesos Estocásticos con Aplicaciones. Área metropolitana de Barranquilla (Colombia): LA IMPRENTA EDITORES.
dc.relationCampo, E. A., Jose Alejandro Cano, J. A., & Rodrigo Gómez, A. (2018). Linear Programming for Aggregate Production Planning in a Textile Company. Fibres & Textiles in Eastern Europe.
dc.relationCornelius T, L. (2018). Intelligent Systems: Technology and Applications, Six Volume Set. WashingtoN, D.C: CRC Press.
dc.relationCorrea León, S. (2018). Sistema analítico para la contabilidad, los costos y la finanzas: con alto contenido de valor agregado a la funcionabilidad del sistema. Ciudad de México: Editorial Ciudad Educativa.
dc.relationCorrea, R. (2018). Gestión de almacenes. Madrid.
dc.relationCruz Fernández, A. (2018). Planificación y gestión de la demanda. COML0210. Málaga - España: IC EDITORIAL.
dc.relationDiaz, D. (2016). Insituto areonautico universitario.
dc.relationDinero. (07 de Enero de 2021). Gremios colombianos piden frenar la importación de leche desde EE.UU. Obtenido de Dinero: https://www.dinero.com
dc.relationFedegan. (27 de Octubre de 2019). Cifras de referencia del sector ganadero. Obtenido de Federación Colombiana de Ganaderos: www.fedegan.org.co
dc.relationGhiyazsinasab, M., Lehoux, N., Menard, S., & Cloutier, C. (2020). Production planning and project scheduling for engineer-to-order systems- case study for engineered wood production. Quebec, Canada: Taylor&Francis.
dc.relationGómez Gómez, I., & Brito Aguilar, J. G. (2020). ADMINISTRACIÓN DE OPERACIONES. GUAYAQUIL ECUADOR: Britto Consulting & Teaching.
dc.relationHernandez, N. R., Lora Freyre, R. J., Moreno Garcia, R. R., Parra Perez, K. M., & Fajardo Alcolea, E. (2017). Planificación de la producción industrial con enfoque integrador asistido por las tecnologías de la información. Retos de la Dirección. Obtenido de Scielo.: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S2306-91552017000100004
dc.relationjablonsky , J., & Skocdopolova, V. (2017). Analysis and Optimization of the Production Process in a Milk Processing Company. The serene, Technological Infromation.
dc.relationKiran, D. (2019). Production Planning and Control: A Comprehensive Approach. Chennai,India: Butterworth-Heinemann.
dc.relationM. Kopanos, G., & Puigjaner, L. (2019). Solving Large-Scale Production Scheduling and Planning in the Process Industries. Basilea, Suiza: Springer Nature Switzerland.
dc.relationMartínez Salazar, I. A., & Vértiz Camarón, G. (2015). Investigaciones de operaciones. México: Grupo Editorial Patria.
dc.relationMonsalve, F. G. (2018). Planificación de Operaciones de Manufactura y servicios. Medellín: Editorial ITM.
dc.relationOchoa, A. (2017). Modelos y modelización.
dc.relationOrquendo, F. (2016). Cálculo de capacidades de producción iniciales Óptimas considerando elementos de incertidumbre.
dc.relationPalacios, A. (22 de 08 de 2017). Asoleche. Obtenido de https://asoleche.org/
dc.relationPayseo Díaz, F. J. (2018). Lean Manufacturing.
dc.relationPedraza Regalado , C. M., & Zúñiga Vásquez Illarek del Rosario, I. (2017). Planeación y control de la producción aplicando el plan maestro,plan agregado y MPR para incrementar la producitividad en la empresa RENISAL.
dc.relationPeña, C. (2017). Planificación de ventas y operaciones. S&OP en 14 claves. Barcelona, España: marge books.
dc.relationphpsimplex. (2000). PHPSimplex Optimizando recursos con Programación Lineal. Obtenido de http://www.phpsimplex.com/casos_reales.htm
dc.relationPonomarev, A. V. (2014). Predicción de series temporales: aplicaciones a la cadena de suministro de petróleo y gas aguas arriba. ELSELVIER.
dc.relationPROPAIS. (2018). Caracterización del Segundo Eslabón de la Cadena Láctea Valle de Ubaté y Chiquinquirá. Bogotá.
dc.relationRajgopal, J. (30 de april de 2014). PRINCIPLES AND APPLICATIONS OF OPERATIONS RESEARCH. Obtenido de https://www.pitt.edu/~jrclass/or/or-intro.html
dc.relationRodríguez Carrazco, J. M. (2015). Taylorismo, La revolución mental que llega a Europa. Madrid: UNED. UNIVERSIDAD NACIONAL DE EDUCACION A DISTANCIA.
dc.relationSantiago, M. D. (2008). Factores determinantes en la gestión de recursos humanos en empresas de servicios que incorporan de manera sistemática nuevas tecnologías Un estudio de caso en la comunidad valenciana. Pensamiento y Gestión, Scielo.
dc.relationSheremetov, L. B. (2016). Econometría: modelos econométricos y series temporales. Vol. II. Córdoba, España: Editorial Reverté; 1er edición .
dc.relationTrujillo , N. (2016). Admisnitración de los inventarios, un marco de administración a corto plazo.
dc.relationValencia Nuñez, E. R. (2017). Investigación operativa. UTA.
dc.relationYaghin, R. G. (2020). Enhancing supply chain production-marketing planning with geometric multivariate demand function (a case study of textile industry). Tehran, Iran: ELSEVIER.
dc.relationZhang, J. (2017). Multi-Agent-Based Production Planning and Control. Hoboken, Nueva Jersey United States: John Wiley & Sons.
dc.relationSocconini, L. (2008). Lean Manufacturing. Paso a Paso. Barcelona, España: ICG Marge, SL.
dc.relationYaghin, R. G. (2020). Enhancing supply chain production-marketing planning with geometric multivariate demand function (a case study of textile industry). Tehran, Iran: ELSEVIER.
dc.relationZhang, J. (2017). Multi-Agent-Based Production Planning and Control. Hoboken, Nueva Jersey United States: John Wiley & Sons.
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/2.5/co/
dc.rightsAbierto (Texto Completo)
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.rightsAtribución-NoComercial-SinDerivadas 2.5 Colombia
dc.titleDiseño de una propuesta de mejoramiento de la planeación agregada de una empresa del sector lácteo mediante un modelo de programación lineal.


Este ítem pertenece a la siguiente institución