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Implementación de un método para el pronóstico de demanda de computadores portátiles
dc.rights.license | Atribución-NoComercial-SinDerivadas 4.0 Internacional |
dc.contributor.advisor | Bula, Gustavo Alfredo |
dc.contributor.author | Garavito Veléz, Karen Briyith |
dc.date.accessioned | 2021-07-09T21:16:28Z |
dc.date.available | 2021-07-09T21:16:28Z |
dc.date.issued | 2021 |
dc.identifier.uri | https://repositorio.unal.edu.co/handle/unal/79792 |
dc.description | ilustraciones, diagramas |
dc.description.abstract | En la búsqueda de las empresas por aumentar su rentabilidad y ofrecer un nivel de servicio adecuado se implementan herramientas para lograr ese objetivo. En este trabajo se hace uso de la implementación del modelo con enfoque jerárquico propuesto por Radim Lenort Petr Besta en el año 2013 para construir el pronóstico de la demanda de los productos de la categoría hardware línea computador portátil para una compañía comercializadora con modelo de negocio B2B (business to business/empresa a empresa). En el proceso de implementación se realiza previamente una depuración de los datos y se genera el pronóstico de la demanda agregada por subcategoría y por línea con el modelo ARIMA, luego se implementa el modelo con enfoque jerárquico para obtener desagregación del pronóstico de la demanda para la línea de computadores portátiles en función de las proporciones históricas. El trabajo se divide en dos fases. En la primera fase se lleva a cabo una revisión sistemática de la literatura para identificar los modelos que han sido usados en la construcción de predicciones de la demanda de productos similares en mercados semejantes al colombiano y en la segunda fase se implementa el modelo con los datos de la empresa en estudio y se analizan los resultados. Al verificar las investigaciones de la industria en estudio la mayoría se enfocan en los eslabones de fabricante y mayorista, a medida que se va en la cadena de suministro aguas abajo se identifica un cambio en el comportamiento de la demanda para el eslabón distribuidor gracias a la cantidad de empresas, el tipo de cliente y el manejo del sistema de inventario pull. Se identifica el modelo propuesto por Lenort en la industria de moda como homóloga a la industria en estudio en su comportamiento de demanda para el eslabón distribuidor. Varios estudios en la industria moda se enfocan en redes neuronales haciendo frecuente precisión en el requerimiento de gran cantidad de datos. La industria de alta tecnología se caracteriza por ciclos de vida cortos lo que limita la cantidad de datos históricos. Se considera que los modelos de redes neuronales son de difícil implementación en la práctica diaria por los recursos requeridos para el entrenamiento de las redes y la elección de los parámetros. El enfoque busca tener un impacto en la facilidad de adopción y la implementación del modelo propuesto y generar eficiencia en los costos ocultos de mantenimiento de inventario, orientados a: depreciación por obsolescencia, tasas de interés por apalancamiento de capital y costos de oportunidad. Con la implementación del modelo propuesto se obtiene un ahorro de $306 millones anuales en los costos ocultos de mantenimiento de inventario relacionados. De los $306 millones, $296 millones se obtienen de la limpieza de los datos y $10 millones por el cambio en el uso del modelo promedio móvil simple al modelo ARIMA con posterior implementación del modelo con enfoque jerárquico. (Apartes del texto) |
dc.description.abstract | In the search of companies to increase their profitability and offer an adequate level of service, tools are implemented to achieve this objective. In this search, the implementation of the model with a hierarchical approach proposed by Radim Lenort Petr Besta in 2013 is used to build the forecast of demand for the products of the category hardware laptop line for a retailer company with a B2B business model (business to business / business to business). In the implementation process a data refinement is previously performed and the forecast of aggregate demand is generated by subcategory and by line with the ARIMA model, then the model is implemented with a hierarchical approach to obtain a breakdown of the demand forecast for the laptop line based on historical proportions. The work is divided into two phases. In the first phase, a systematic literature review to identify the models that have been used in the construction of predictions of the demand for similar products in markets similar to Colombia, and in the second phase the model is implemented with data from the company and the results are analyzed. When verifying the state of the art of the industry under study, most of them focus on the manufacturer and wholesaler links, as one goes in the downstream supply chain a change in the behavior of demand for the distributor link is identified by the quantity of companies, the type of client and the management of the pull inventory system. The model proposed by Lenort in the fashion industry is identified as homologous to the high-tech industry by the behavior of demand for the distributor link. Several studies in the fashion industry focus on neural networks making precision in the requirement of large amounts of data. The high-tech industry is characterized by short life cycles, which limits the amount of historical data. Neural network models are considered as difficult to implement in daily practice due to the resources required for the training of the networks and the choice of parameters. The approach seeks to have an impact on the ease of adoption and implementation of the proposed model and generate efficiency in the hidden costs of inventory maintenance by depreciation due to obsolescence, interest rates due to capital leverage and opportunity costs. With the implementation of the proposed model, savings of $ 306 million per year are obtained in related hidden inventory maintenance costs. Of the $ 306 million, $ 296 million are by the data cleaning and $ 10 million by the change in the use of the simple moving average model to the ARIMA model with subsequent implementation of the model with a hierarchical process. (Text taken from source) |
dc.format.extent | 125 páginas |
dc.format.mimetype | application/pdf |
dc.language.iso | spa |
dc.publisher | Universidad Nacional de Colombia |
dc.rights | Derechos reservados del autor |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.subject.ddc | 620 - Ingeniería y operaciones afines |
dc.title | Implementación de un método para el pronóstico de demanda de computadores portátiles |
dc.type | Trabajo de grado - Maestría |
dcterms.audience | General |
dc.type.version | info:eu-repo/semantics/acceptedVersion |
dc.publisher.program | Bogotá - Ingeniería - Maestría en Ingeniería - Ingeniería Industrial |
dc.description.degreelevel | Maestría |
dc.description.degreename | Magíster en Ingeniería Industrial |
dc.description.researcharea | Gestión de operaciones |
dc.identifier.instname | Universidad Nacional de Colombia |
dc.identifier.reponame | Repositorio Institucional Universidad Nacional de Colombia |
dc.identifier.repourl | https://repositorio.unal.edu.co/ |
dc.publisher.department | Departamento de Ingeniería de Sistemas e Industrial |
dc.publisher.faculty | Facultad de Ingeniería |
dc.publisher.branch | Universidad Nacional de Colombia - Sede Bogotá |
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dc.rights.accessrights | info:eu-repo/semantics/openAccess |
dc.subject.proposal | Pronóstico |
dc.subject.proposal | Previsión |
dc.subject.proposal | Hardware |
dc.subject.proposal | Alta tecnología |
dc.subject.proposal | Demanda |
dc.subject.proposal | Portátil |
dc.subject.proposal | Forecasting |
dc.subject.proposal | Forecast |
dc.subject.proposal | Laptop |
dc.subject.proposal | High-tech |
dc.subject.proposal | Demand |
dc.subject.unesco | Comportamiento económico |
dc.subject.unesco | Consumo |
dc.subject.unesco | Ordenador |
dc.title.translated | Implementation of a method for the demand forecast for laptops |
dc.type.coar | http://purl.org/coar/resource_type/c_bdcc |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa |
dc.type.content | Image |
dc.type.content | Text |
dc.type.redcol | http://purl.org/redcol/resource_type/TM |
oaire.accessrights | http://purl.org/coar/access_right/c_abf2 |
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