Model for the simulation of the production of handmade men's footwear in Bogotá, Colombia

ilustraciones, diagramasLa producción de calzado masculino hecho a mano es una industria de tradición en Bogotá, donde existen numerosas fábricas y talleres que ofrecen productos hechos a mano con un enfoque en la calidad y la atención al detalle. Esta industria es conocida por su variedad de diseños y estilos, se distingue por su autenticidad y la habilidad de los artesanos. Esta industria enfrenta varios desafíos, como la competencia de productos de producción en masa, la escasez de materiales y los riesgos asociados a que sea un proceso manual que en muchas ocasiones no está estandarizado. Considerando principalmente el ultimo desafío, se realiza este trabajo que buscara implementar políticas que optimicen la producción del calzado. De este trabajo, se puede concluir que es posible optimizar la producción reduciendo los tiempos de espera, con la implementación de modelos de aprendizaje por refuerzo entrenados desde una simulación por eventos descritos. (Texto tomado de la fuente)Handmade men's shoe production is a traditional industry in Bogotá, where there are numerous factories and workshops offering handmade products with a focus on quality and attention to detail. This industry is known for its variety of designs and styles, and is distinguished by its authenticity and the skills of the artisans. This industry faces various challenges, such as competition from mass-produced products, scarcity of materials, and risks associated with being a manual process that is often not standardized. Considering mainly the last challenge, this work aims to implement policies to optimize shoe production. From this work, it can be concluded that it is possible to optimize production by reducing wait times, with the implementation of reinforcement learning models trained from a simulation based on described events.MaestríaMagíster en Ingeniería - AnalíticaAnalíticaÁrea Curricular de Ingeniería de Sistemas e Informátic

Optimal Reconfiguration of Complex Production Lines for Profit Maximization via Simulation Modeling

With the recent trend of re-shoring, transferring manufacturing systems from a workforce-intensive to a capital-intensive production environment becomes more common. One challenge multinational manufacturing companies may face in such an endeavor is reconfiguration of the transferred manufacturing system according to the availability of better machinery in the capital-intensive environment. In this dissertation, based on a real-life problem, I develop several simulation optimization methods for the problem of production line reconfiguration. The case is a reverse transfer of manufacturing system/technology, i.e. transfer from a workforce-intensive environment to a capital-intensive one. I investigate the performances of nine different simulation optimization approaches based on the real-life case in automotive industry to illustrate their relative strengths under different parameter scenarios. I also create a test-bed problem to determine the specifications of these methods, and further analyze their performances. Numerical results may guide the practitioners facing similar challenges in choosing a suitable solution approach depending on the problem size and solution time availability