This master thesis presents a practical framework for integrating Simulation-Based Optimization into facility layout studies. While various methodologies exist for improving facility layouts and the utilization of Simulation-based Optimization, there is a gap in practical frameworks offering a systematic approach to combine these methods effectively. Existing frameworks lack specificity, require substantial prior knowledge, and offer limited insight into the methodologies employed. Consequently, there is a need for a comprehensive, step-by-step framework accessible to a broader range of practitioners. The proposed framework addresses this gap by providing a practical step-by-step approach that guides practitioners through a Simulation-Based Optimization integrated facility layout study. This framework facilitates the development of alternative layouts and system configurations using trusted methods. To assess the proposed framework, a case study was conducted at a manufacturing facility with the purpose of enhancing the production throughput. The case study followed the steps outlined in the framework in a real-world scenario, which provided valuable insights into the practicality and usefulness of the framework. The framework's effectiveness hinges on careful execution of each step, particularly given its front-loaded nature. Neglecting any step could lead to inaccuracies in subsequent stages, undermining the overall validity of the study. Adequate time allocation, especially in data collection and simulation model development, is critical to ensuring robust results. While the framework's applicability has been demonstrated in a high-mix low-volume production environment, its broader effectiveness across different settings remains to be explored. Nonetheless, the framework's intuitive flow and reliance on established methodologies enhance its usability and potential to improve production system throughput. Ultimately, the study contributes a tangible solution to the research question, offering practitioners a valuable tool for streamlining production.

La capacidad y las buenas prácticas de producción son base para el desarrollo de las empresas y más con la competitividad actual. Por ello, el caso de estudio presentado analiza las operaciones de una MYPE peruana del sector plástico, que habría dispuesto previamente mudarse a una nueva planta. En base a un diagnóstico se identificó un déficit en su capacidad de producción con costos representativos equivalentes al 9% de su facturación anual, derivados de la falta de máquinas e ineficiencias, las cuales aun siendo solucionadas no permitirían satisfacer la demanda, por lo que se confirmó que la decisión de la empresa era correcta. De tal forma, se planteó un proyecto que permitiría el diseño de las nuevas instalaciones de la empresa en un local de mayores dimensiones, con el objetivo de optimizar su capacidad de producción y evitar que las malas prácticas detectadas en la actualidad se repitan, validando su viabilidad mediante un prototipo virtual. Asimismo, en base a los cálculos se lograría aumentar la capacidad instalada en 53.5%, superando a la demanda proyectada dentro de tres años en un 24.90 %, lo que permitiría un mayor crecimiento organizacional en el futuro. / The capacity and good production practices are the basis for the development of companies and more with the current competitiveness. Therefore, the case study presented analyzes the operations of a Peruvian MSE in the plastics sector, which would have previously arranged to move to a new plant. Based on a diagnosis, a deficit in its production capacity was identified with representative costs equivalent to 9% of its annual turnover, derived from the lack of machines and inefficiencies, which, even being solved, would not allow to satisfy the demand, therefore confirmed that the company's decision was correct. In this way, a project was proposed that would allow the design of the company's new facilities in a larger premises, with the aim of optimizing its production capacity and preventing the bad practices detected at present from being repeated, validating their viability through a virtual prototype. Furthermore, based on the calculations, it would be possible to increase the installed capacity by 53.5%, surpassing the projected demand in three years by 24.90%, which would allow greater organizational growth in the future. / Trabajo de investigación

[ES] La planificación de la distribución espacial en plantas industriales (FLP) es una de las decisiones más importantes en el contexto de la dirección de operaciones, y uno de los problemas de mayor discusión en la literatura científica enmarcada en el campo amplio de la ingeniería industrial. Sin embargo, el uso generalizado del enfoque de solución top-down tradicional, que se inicia con el diseño de la distribución del conjunto de los departamentos o celdas de trabajo que conforman el sistema de producción y prosigue con la distribución detallada al interior de éstos, parte de asunciones poco compatibles con la realidad operacional industrial que implican ciertas limitaciones para su adopción en la práctica. Esto, unido al hecho de que los modelos matemáticos empleados en la generación de alternativas de layout utilizan en su mayoría el coste de manejo de materiales como una función monoobjetivo de carácter cuantitativo, desvirtuando la naturaleza multiobjetiva del problema, acentúa un vacío que genera oportunidades de mejora en la toma de decisiones de planificación del layout en la práctica industrial. En este contexto, esta tesis doctoral, respaldada por un estudio minucioso del estado del arte y el análisis de modelos de optimización matemática de referencia, presenta un marco conceptual para la toma de decisiones de planificación del FLP desde una perspectiva multiobjetivo, y un nuevo modelo de optimización multiobjetivo no lineal entero mixto (MOMINLP) para facilitar la toma de decisiones de distribución espacial en plantas industriales metalmecánicas en entornos de demanda dinámicos mediante un enfoque de planificación bottom-up, teniendo en cuenta criterios cuantitativos y cualitativos. El modelo propuesto, denominado bottom-up mDFLP, considera tres funciones objetivo que pretenden: (1) minimizar el coste total de manejo de materiales y el coste total de reorganización, (2) maximizar el rating de proximidad subjetiva entre departamentos, y (3) maximizar el ratio de utilización de área. El modelo bottom-up mDFLP ha sido validado en una empresa del sector metalmecánico, confirmando un mejor desempeño en los valores de las funciones objetivo respecto a los obtenidos en la distribución en planta actual. / [CA] La planificació de la distribució espacial en plantes industrials (FLP) és una de les decisions més importants en el context de la direcció d'operacions, i un dels problemes de major discussió en la literatura científica emmarcada en el camp ampli de l'enginyeria industrial. No obstant això, l'ús generalitzat de l'enfocament de solució top-down tradicional, que s'inicia amb el disseny de la distribució del conjunt dels departaments o cel·les de treball que conformen el sistema de producció i prossegueix amb la distribució detallada a l'interior d'aquests, part d'assumpcions poc compatibles amb la realitat operacional industrial que impliquen unes certes limitacions per a la seua adopció en la pràctica. Això, unit al fet que els models matemàtics emprats en la generació d'alternatives de layout utilitzen en la seua majoria el cost de maneig de materials com una funció monoobjetivo de caràcter quantitatiu, desvirtuant la naturalesa multiobjectiva del problema, accentua un buit que genera oportunitats de millora en la presa de decisions de planificació del layout en la pràctica industrial. En aquest context, aquesta tesi doctoral, recolzada per un estudi minuciós de l'estat de l'art i l'anàlisi de models d'optimització matemàtica de referència, presenta un marc conceptual per a la presa de decisions de planificació del FLP des d'una perspectiva multiobjectiu, i un nou model d'optimització multiobjectiu no lineal enter mixt (MOMINLP) per a facilitar la presa de decisions de distribució espacial en plantes industrials metallmecàniques en entorns de demanda dinàmics mitjançant un enfocament de planificació bottom-up, tenint en compte criteris quantitatius i qualitatius. El model proposat, denominat bottom-up mDFLP, considera tres funcions objectiu que pretenen: (1) minimitzar el cost total de maneig de materials i el cost total de reorganització, (2) maximitzar el rating de proximitat subjectiva entre departaments, i (3) maximitzar el ràtio d'utilització d'àrea. El model bottom-up mDFLP ha sigut validat en una empresa del sector metallmecànic, confirmant un millor acompliment en els valors de les funcions objectiu respecte als obtinguts en la distribució en planta actual. / [EN] Facility layout planning (FLP) is one of the most critical decisions in operations management and one of the most discussed problems in the scientific literature framed in the broad field of industrial engineering. However, the widespread use of the traditional top-down solution approach, which starts with a block layout design phase and continues with the detailed layout within each work cell making up the production system, is based on assumptions that are not very compatible with the industrial operational reality, which implies certain limitations for its adoption in practice. This issue, together with the fact that the mathematical models used in the generation of layout alternatives mostly use the cost of material handling as a single objective function of a quantitative nature, distorting the multi-objective nature of the problem, accentuates a gap that generates opportunities for improvement in the FLP decision making process in industrial practice. In this context, this doctoral thesis, supported by a thorough study of state of the art and the analysis of benchmark mathematical optimisation models, presents a conceptual framework for FLP planning decision making from a multi-objective perspective and also a new multi-objective mixed-integer non-linear optimisation model (MOMINLP) to facilitate FLP decision making for metal-mechanical industrial plants in dynamic demand environments through a bottom-up planning approach, taking into account quantitative and qualitative criteria. The proposed model, called bottom-up mDFLP, considers three objective functions that aim to: (1) minimising the total material handling cost and the total rearrangement cost, (2) maximising the subjective closeness rating between departments, (3) maximising the area utilisation ratio. The bottom-up mDFLP model has been validated in a company from the metal-mechanical sector, confirming a better performance in the values of the objective functions than those obtained in the current plant layout. / Pérez Gosende, PA. (2022). Enfoque multiobjetivo bottom-up para la planificación dinámica de la distribución espacial en plantas industriales [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/185800

<p>The construction industry contributes significantly to the GDP of the United States, attributing to its growth at an unprecedented rate. Efficient planning on all stages of construction is the only way to combat dynamic obstructions and deliver projects on time. The first element involved in the planning phase deals with the layout of the Construction Site. It significantly regulates the pace at which construction operations function and directly affects the time, cost, and safety linked to the successful delivery of the target project. Hence, it is paramount to ensure that every component of the construction site maneuvers with the utmost productivity. One such equipment that occupies significant attention while carrying out the CSLP process is Tower Crane. Tower crane optimization is pivotal to ensure proper lifting and handling of materials, and warrant conflict-free work zones. This research, therefore, aims to optimize its position by maximizing the lift ability. To achieve the goals, Generative Design- a paradigm that integrates the constructive features of mathematical and visual optimization techniques, is used to develop a relatively comprehensible prototype. The first part of the research, thus, utilized Generative Design on two construction sites- one from the United States and one from India. After implementing the visual programming algorithm, an improvement of 40% was warranted in the lift score. A pool of potential alternatives was explored and supplemented by the trade-off illustrations. The concept of trade-off was substantiated by allowing a framework for prioritization of lift cycles, and facilitating a holistic decision-making process. To evaluate the usability, 12 participants were chosen based on their previous experience with tower crane operations. The participants witnessed a live demonstration of the algorithm, answered a Likert scale questionnaire, and appeared for an open-ended interview to provide feedback about the proposed Generative Design technique. After carrying out narrative analysis for the usability aspect- it has been unanimously observed that the technique has extreme efficiency of usage and can evidently prevent the occurrence of errors. The study concludes by providing recommendations to augment the significance and usability of Generative Design for tower crane position optimization. </p><br>