Ingeniería

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Diseño de vaso linfático artificial en el tratamiento de linfedema secundario por cáncer de mama
(2022)
Durán Aguilar, Gabriela
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Rosa Sierra, Luis Alberto
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Fuentes Aguilar, Rita Quetziquel
El cáncer de mama es el tumor maligno que más frecuentemente afecta a las mujeres, tanto en Estados Unidos y Europa, así como en México. Como efecto adverso al realizar los tratamientos de este padecimiento, en la mayoría de los casos surge el linfedema secundario asociado al cáncer de mama. Esta complicación ocurre como resultado de la interrupción del flujo linfático en las extremidades superiores en conjunto a otros factores tales como radiación, sedentarismo, extracción de ganglios, daños en los vasos linfáticos, entre otras. En este proyecto de tesis se analizaron los cambios en los patrones de incidencia, mortalidad y supervivencia en cáncer de mama confirmando que, específicamente el padecimiento del linfedema tiene un alto impacto sanitario, social y económico, teniendo en cuenta que afecta fundamentalmente a mujeres en edades tempranas y que en un tercio de los casos se convierte en una enfermedad crónica. Por lo que se hace imprescindible la rehabilitación para una mejor calidad de vida en las pacientes que sobreviven de esta enfermedad. Actualmente existen tratamientos manuales, farmacológicos y cirugías para disminuir la alteración que sufre el paciente con linfedema; sin embargo, el éxito de los tratamientos depende de las características de cada paciente. Ante dicha problemática se planteó el diseño de un prototipo de vaso linfático para asistir la insuficiencia mecánica del sistema linfático dañado. A lo largo de este proyecto de tesis de grado se presenta la metodología de diseño utilizada, para el diseño de vaso linfático. Se espera que el cirujano pueda implantar, en un futuro, el prototipo de vaso linfático para restablecer con él la circulación de la linfa a través del sistema linfático, ayudando así al combate del linfedema.
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Método de Inicios Fijos en Planeación de Obra de Construcción de tipo Repetitivo
(2021)
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Orozco Argote, Francisco Alejandro
Dentro de la industria de la construcción, se presentan muchos problemas para entregar proyectos en tiempo; estos problemas son causados por muchas variables (mano de obra, proyectos, planeación, entre otros); en esta investigación, se pretende proponer la reducción de la variabilidad de las entregas de los proyectos en construcciones del tipo repetitivas. Esta reducción se pretende obtener mediante la implementación de la metodología que denominaremos: “Método de Inicios Fijos” (Fixed Start Method, FSM). Este método FSM reduce la variabilidad de la entrega de los proyectos utilizando restricciones fundamentales en el proyecto, las cuales son: el uso de inicios fijos en las actividades y el establecimiento de duraciones planeadas con un alto porcentaje de certidumbre de cumplimiento. Así pues, se pretende que, en la etapa de planeación de los proyectos, se utilicen duraciones con un 95 % de confianza de cumplimiento estadístico. De esta manera, se asegurar que la duración introducida dentro de la etapa de planeación se cumpla. Además, al asentar estas duraciones, mediante el método de líneas de balance, se determina cuándo serán los inicios y términos de cada una de las actividades. El modelo FSM se comprobó mediante el uso de dos casos de estudio. En el primero, se tienen viviendas de dos niveles, con datos históricos y comportamiento secuencial continuo. En el segundo caso, se presentan lotes de vivienda de un solo nivel. Se procedió en ambos casos a simular los eventos, para los cuales se obtuvieron resultados positivos en los que se redujo la variabilidad de las entregas de los proyectos, mostrando la utilidad y posible factibilidad de implementación de la herramienta en proyectos reales.
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Algorithms for Supplier Selection and Order Quantity Allocation
(2020)
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Mendoza Andrade, Abraham
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Olivares Benitez, Elías
Supply chain management is particularly important because of its influence on a compan\¶s profitabilit\ and competitiYeness. Among the different actiYities inYolYed in supply chain management, purchasing decisions, supplier selection, and order quantity allocation have a direct impact on the cost of the produced items. The cost function usually deals with non-linear equation systems with an infinite number of possible solutions. The result is an optimal inventory policy with a minimum cost per time unit. This research addresses the supplier selection and order quantity allocation problem. The objective is to allocate the corresponding order quantities over time to the selected suppliers, while minimizing inventory and transportation costs, simultaneously. In selecting suppliers, two feasibility constraints are considered: capacity and quality (perfect rate). Typically, in the literature, the acceptable perfect quality rate of raw materials is ensured with a mathematical inequality in the model constraints. Therefore, this research first addresses the desired perfect rate by including it as part of the order cycle parameters calculation and not as an individual constraint. The main advantages of doing so are: (i) it leads to lower-cost solutions compared to previously proposed literature, (ii) it effectively faces the so-called low perfect rate situations, by providing feasible solutions when the perfect rate of suppliers is smaller than the minimum perfect-rate required by the customer. A sensitivity analysis was carried out on the proposed model to analyze the effect of some parameters on the total cost per time unit. Results showed that transportation costs have an important effect on the order quantity and that the price levels do not necessarily affect the number of purchased units. Hence the importance of considering transportation costs when making order quantity allocation decisions. Another challenge of the problem under study is that the model is non-linear and has an infinite number of possible solutions because of the continuous nature of the variables. Therefore, there is a need from the scientific and industry communities to find solutions in an efficient and timely manner. Former studies introduced limits to the length of the order cycle or to the number of orders in the order cycle in order to obtain a solution using commercial software. However, computers still take many hours or days to provide optimal solutions, if at all. Therefore, second, this research applies different metaheuristic algorithms to solve the problem, namely: particle swarm optimization (PSO), genetic algorithm (GA), and differential evolution (DE). With these algorithms, a larger solution space can be explored while getting a solution in the order of seconds; this allows cheaper solutions to be found. PSO, GA, and DE are well known metaheuristic algorithms in the optimization field and have been used to solve lot-sizing, and supplier selection problems. New metaheuristic methods are commonly proposed for particular circumstances, for example, converging to an optimal solution faster than other strategies. A recently proposed metaheuristic algorithm, the Grey Wolf Optimizer (GWO), was explored in this research. The algorithm was modified and adapted to the supplier selection and order quantity allocation problem when the amount of decision variables is too large. The improved GWO method, called iGWO, includes weighted factors and a displacement vector to promote the exploration of the search strategy avoiding the use of unfeasible solutions. The iGWO was tested and results showed that, in addition to obtain optimal solutions, it performed a better search strategy, finding feasible solutions in all instances of the tested problem. Finally, based on the knowledge acquired through the previous contributions, a heuristic algorithm to solve the problem under study is proposed. This heuristic algorithm allows to extend the explored solution space to an exceptionally large limit. The solutions obtained with the proposed heuristic algorithm were compared against the solutions obtained with PSO and DE. Two numerical examples are solved. In the first one, it is shown that the proposed heuristic performed best compared to other solutions previously published in the literature, both in terms of computational time and total cost. In the second numerical example, larger instances were studied. Our findings show that the proposed heuristic was able to find a feasible solution, while PSO and DE were unable to find a solution. Therefore, the proposed heuristic does not just lead to lower total cost solutions, but it also performs a more exhaustive search in shorter computational times for larger instances of the problem.
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Propuesta de un proceso de diseño para el desarrollo de dispositivos médicos, basado en jerarquías de usuarios.
(2023)
Cortés Chávez, Fabiola
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Rosa Sierra, Luis Alberto
The lack of knowledge about users during the development of new medical devices, deepening the decrease in the importance of the implementation of ergonomic factors during the design process, as well as the rigorous regulations that govern medical device design. During the design process of medical devices, all the users involved must be hierarchical considered, prioritizing the needs of each user, according the movement of patient health stage, since this information is fundamental for the task analysis, the evaluation of the multiple future scenarios that they make up and therefore the relationship with all the functions of the product and the final characteristics of the object. Concluding that the design process based on hierarchies allows the designer to have a better understanding of the needs of all users, by using the design process of a new stretcher, it effectively generates an increase in user acceptance compared to the traditional design process. This study will help medical device designers to make decisions based on the functions and features required in the product during the development stage. In addition to helping researchers with the didactics of the design process, demonstrating the importance of the correct execution of the process and how the factors considered can have a greater impact on the acceptance of the product by users.
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Métodos de solución para problemas de secuenciación en máquinas paralelas no relacionadas
(2023)
García de Alba Valenzuela, Héctor Roberto
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Nucamendi Guillen, Samuel Moises
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Avalos Rosales, Oliver
En los entornos productivos se presentan constantemente situaciones en las que se tiene un conjunto de actividades por realizarse, un conjunto de máquinas capaces de realizar dichas tareas, y se debe decidir cómo se debe de repartir la carga de trabajo y en qué orden se deben de realizar dichas actividades. Estos sistemas se estudian en las disciplinas de optimización combinatoria bajo los conceptos de secuenciación, y son relevantes en la industria debido a las grandes implicaciones económicas asociadas al uso de recursos que dichas decisiones impactan en diversas aplicaciones, como lo puede ser las industrias de impresión, manufactura de herramentales o artículos personalizados y de alta precisión, talleres de manufactura flexible, entre otras. En este trabajo de investigación se estudian dos tipos de problemas de secuenciación. El primero consiste en un problema de secuenciación en máquinas paralelas no relacionadas con minimización de la tardanza total, mientras que el segundo se encuentra relacionado con la secuenciación en máquinas paralelas no relacionadas con minimización de makespan, tiempos de preparación dependientes de la secuencia y recurso compartido. Para el primer problema se presentan 2 metodologías de solución: la primera utiliza un modelo de programación lineal entera mixta basado en variables de posición, el cual no necesita de restricciones de gran M e incorpora desigualdades válidas para acelerar su ejecución, y como segunda metodología se presenta un algoritmo metaheurístico de búsqueda local iterada con estrategias de mejora basadas en mecanismos de reinserción e intercambio de tareas. El segundo problema bajo estudio considera una extensión del problema de recursos compartidos, donde dicho recurso ejecuta todos los procesos de preparación y debe de tener una secuencia propia de actividades. Esta secuencia, a su vez, está ligada a las secuencias de las distintas máquinas del sistema, visualizando así al recurso compartido como una máquina. Para este problema se exploran 2 metodologías de solución; primero un conjunto de modelos (6 específicamente) de programación lineal entera mixta que describen el sistema desde varias perspectivas relacionadas a hitos de tiempo del sistema. La segunda metodología de solución contempla un par de algoritmos metaheurísticos de descenso por vecindarios variables (4 mecanismos de generación de vecindarios), e incorpora dos mecanismos de diversificación. Para el primer problema se tuvo la oportunidad de comparar el desempeño del modelo matemático contra un modelo previamente presentado en la literatura, demostrando su superioridad al obtener soluciones óptimas en instancias donde el modelo previo reportaba soluciones factibles con hasta 74% de gap. Adicionalmente, se mejoró el desempeño del modelo propuesto mediante la inclusión de desigualdades válidas, resultando en reducciones de hasta un 30% en tiempo de procesamiento. Para el segundo problema se consideraron 6 formulaciones distintas, basadas en diferentes momentos de referencia relevantes para el sistema, con lo que se determinó que las formulaciones que usan como referencia el tiempo de terminación del proceso de preparación tienen mejor desempeño. Para ambos problemas se realizaron comparativas entre los modelos y los algoritmos propuestos correspondientes, con el fin de determinar la capacidad de los algoritmos para encontrar soluciones de alta calidad. Los resultados experimentales muestran que los algoritmos propuestos son competitivos. Además, para el primer problema se lograron abordar instancias de hasta 400 tareas mediante dicho algoritmo, mientras que, para el segundo, se resuelven instancias de hasta 60 tareas.
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Maintenance 5.0: A human-in-the-Loop-based Framework for Industrial Physical Assets Resilience
(2023)
Cortés Leal, Alejandro
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Del Valle Soto, Carolina
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Cárdenas Pérez, César Raúl
Due to the global uncertainty caused by social problems such as COVID-19, the microchip crisis, and cybersecurity attacks, many companies have opted to use emerging technologies since they allow them to maintain productivity in challenging times, achieving business strategic results. The preceding is based on market studies and research on emerging technologies. One example is in wearable artificial intelligence (AI) and wireless sensor networks (WSNs), the application of which in Industry is growing exponentially. Some social trends that seek to explore the use of AI and sensors to solve these social problems and uncertainty are Society 5.0 (S5.0), Industry 5.0 (I5.0), as well as the so-called AI for Social Good (AI4SG). I5.0 seeks to improve the resilience of industrial processes through sustainable and human-centered strategies; resilience is a metric closely related to the maintenance of physical assets since it can be calculated through performance and time measures in calculating reliability, availability, and safety. To have an approach to the problems of industrial maintenance and to be able to formulate a research question, first maintenance congresses, forums, and social networks were attended, an own initiative of Industry 4.0 was created, and experts were interviewed. The above actions allowed us to understand the industrial maintenance needs and problems more clearly. Secondly, an explorative literature review (ELR) was carried out on the research gaps in industrial maintenance; the gaps that were most consistent with the interest of this research were the following: a) the creation of feedback mechanisms for the state of physical assets; b) intelligent human-machine interaction, synergy, interoperability, and mutual learning; and c) resolve the issue of uncertainty. Third, a comparative table was then made in which the Industry's needs were compared against the selected research gaps. Finally, this comparison helped to justify the research topic: A human-in-the-Loop-based Framework for Industrial Physical Assets Resilience. Intelligent maintenance systems, such as reliability-centered maintenance (RCM), maintenance 4.0 (M4.0), self-healing systems, condition-based maintenance (CBM), and risk-based maintenance, among others, can repair a machine or take care of a physical asset; however, if the automatic and self-repairing system fails or decides out of context, the physical asset is left partially or unprotected, increasing uncertainty in the productive system and requiring external help. Continuous collaboration and communication between machines and workers are necessary to keep physical assets running in an industrial process. Due to the above, one motivation of this research work is to know how including human decisions in intelligent maintenance systems can impact the increase of resilience in physical assets. By including the human-in-the-loop (HITL), the maintenance worker could continue to put his knowledge at the service of the physical assets, which means that he keeps his practical ability to solve problems. Because the above is not considered in other maintenance frameworks, such as Maintenance 4.0, the following main research question (RQ1) has been formulated: could a human-in-the-loop-based maintenance framework improve the resilience of physical assets? This doctoral research examines how industrial physical assets can be protected to increase their resilience by creating a novel Maintenance 5.0 (M5.0) framework with the HITL. Due to the above, a framework for the worker of the future called Worker 5.0 (W5.0) is presented, which is the human being who adds value to the company's value chain through the use of non-intrusive wearables that increase their communication, and through the experience, it shares advising on the AI, so that the decisions that are made do not get out of context; the preceding impacts on an increase in the resilience of the signal that the physical asset is transmitting. Another literature review was conducted, but this time it was a systematic literature review (SLR), taking as keywords: HITL, maintenance, and resilience; with the SLR results, the state of the art was elaborated, and the hypothesis was formulated. With the SLR results and applying a questionnaire survey to experts, Checkland's qualitative and deductive methodology was selected to design a maintenance framework that meets the objectives of Industry 5.0. Within this methodology, to know the goals and answer of the research question, some specific activities were carried out: a) detection of needs and review of the scope of research gaps in maintenance; b) a characterization of work and maintenance throughout industrial history; c) definitions and characteristics of M5.0 and W5.0 are proposed, d) two HITL control loops of M5.0 framework are proposed: the first is an OSA-CBM-inspired, and the second is self-healing-inspired; e) M5.0 general architecture is proposed, which considers the OODA loop, as well as the steps for the creation of value in the company and classifies the activities that must be carried out in the physical world and the cyber world; f) two proposals for the calculation of resilient maintenance: one for real- time processes, inspired by the raised cosine, and another for historical processes, inspired by the Weibull distribution; g) an ease-benefit analysis of the proposed changes to M4.0 to make it M5.0; h) a list of enabling technologies for the proposed maintenance framework noting their impact on I5.0 goals; i) a catalog of wearables was prepared that will help implement W5.0, and M5.0; and finally, j) tools and enablers to implement M5.0 are proposed. In the last step of the methodology, the theoretical proposal must be carried out in the physical world, so the hypothesis is demonstrated through a case study of an Industrial Wireless Sensor Network (IWSN), which refers to a Wireless Sensor Network (WSN) that is immersed in an industrial environment. One of the leading research gaps was the creation of feedback mechanisms of the state of physical assets; at the same time, one of the needs detected in the Industry was the use of wireless and non-intrusive technologies (wearables and IWSNs) to implement remote solutions; due to this, to validate the proposed M5.0 framework, it was decided to carry out a case study, taking an IWSN as a physical asset. The maintenance of the IWSN may vary according to first, a) the inclusion of HITL, which is the primary motivation of this research, and responds to RQ1, and second, b) the improvement in communication between network nodes (physical assets) that make up the IWSN, which responds to RQ2: which Industrial Wireless Sensor Network scheme helps more to protect the network nodes from failure events? IWSNs are physical assets that must be maintained at acceptable levels since they are the ones that make up the base of the automation pyramid, feeding data to industrial control systems. RQ2 is considered a sub-item of RQ1 since it responds to the needs of this case study where M5.0 is being validated. To answer RQ2, a mechanism for the resilience of IWSNs that is based on the measurement of performance metrics and the network scheme is proposed, laying the foundations of the case study; the case study is composed of simulations and experiments that use different densities and network schemes; while the cooperative scheme is more efficient when an IWSN is under normal operating conditions, the collaborative scheme offers more excellent protection against aggressive interference on performance metrics, making it more secure and resilient. In addition, a real-time jamming detection algorithm is proposed with the following characteristics: first, a) it examines the characteristics and damages caused by the type of aggressor; second, b) it reflects the natural immunity of the WSN (which depends on its node density and a cooperative or collaborative configuration); and finally, c) it considers performance metrics, especially those that impact power consumption during sensor transmission. The case study demonstrated that network nodes save more than 10% of energy if they switch their network schemes in the event of interference. Regarding jamming mitigation, it is possible to know the optimal route for delivering communication packets using an AI algorithm; M5.0 is finally validated by including the HITL as a network adviser, which assesses AI algorithms to increase resilience.
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Feedback based dynamic environment system for robot-assisted gait training
(2023)
Rodríguez Muñoz, Arturo Jafet
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Del Valle Soto, Carolina
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González Sánchez, Javier
Computer-aided rehabilitation therapy has evolved at a staggering rate since the combination of mechanics, electronics and software was first introduced over two decades ago. Multiple procedures have been augmented by the use of machines to standardize the therapy and also to have metrics. Therefore, patients who cannot walk properly due to functional gait disorder have experienced an evolution from the traditional approaches of using a walking bar to robot- assisted gait training as shown by Ricklin, Meyer-Heim, and Van Hedel (2018). The main differences reside in having a more controlled environment where the patient can suffer fewer accidents, promote muscle memory through proper movements, and measuring the effort done among other essential data. The Instituto Nacional de Estadística y Geografía (INEGI) creates multiple census and surveys to map the current situation of Mexico. According to INEGI (2021) and INEGI (2017) in Mexico in 2020 the total population is approximately 126 million people where 51.21% are women and 48.78% are men, and 16.53% of the population has an impairment or limitation. In other words, 20.8 million people have at least one of the seven most reported impairments which include walking or climbing stairs using their legs. Unfortunately, robot-assisted gait therapy requires advanced equipment which is expensive. Consequently, it is not intended to be a personal device but instead a medical device available only in hospitals and rehabilitation centers. As a result, the amount of people who can benefit from this technology depends on their location and the availability of each center, so a patient might have to wait several months before starting therapy. Hence, the importance of having high efficiency in each session so that each center can help more people. In this dissertation, we first wondered if having multiple wireless devices on a subject was possible without suffering from data loss due to interference. The challenge comes from the possibility of scalability, in other words, introducing a more abundant amount of devices to collaborate and gather more significant data as time passes. Therefore, we proposed a new predictive tool and a scheme to address the concerns previously stated. The tool and the scheme allow the simulation of environments where multiple consumer devices gather informa- tion from the user regardless of the polling speed or the connection technology employed in a Wireless Sensor Network (WSN). From the tests we ran, we found that it is possible to have an environment where many different sensors can feed a system without losing data, which means that using this simulator, a WSN can be planned for its initial phase or for scaling a previous state. Afterward, we worked on validating that it was possible to use an electroencephalogram with a virtual reality headset on patients that have a neurological condition. We retrieved the affective state using a dedicated framework designed for that purpose. During the study, we found that some of the interpreted values, such as meditation, had a shorter range and variation for the patients with more neurological affectations. Furthermore, introducing virtual reality showed an increase of 16% in the efficiency of the session, which was accomplished with a static scenario. Therefore, we predicted that a dynamic feedback-based scenario could provide better efficiency than a static scenario. Finally, we worked on the final study, creating an adaptive feedback system based on adjusting the background music, visual aid brightness, and overall illumination of a virtual reality environment. The proposed active feedback system successfully increased the active physical effort done by the users.
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Recurso Humano como ventaja competitiva en la Industria de la Construcción y un modelo para determinar sus factores e indicadores.
(2024)
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Orozco Argote, Francisco Alejandro
External and internal agents that modify and define its competitiveness continuously affect the construction industry. Changing markets, currency fluctuations, and tremendous competition have made the issue of competitiveness increasingly important. The literature highlights factors that determine the competitiveness of construction firms, including easy-to-measure elements, such as finances, sales, return on investment, among others. In contrast, other elements are not as easily measurable, such as customer satisfaction, employee satisfaction, loyalty, and leadership, among many others. Within these factors, Human Resources (HR) has occupied a central place in the last decade, due to the enormous impact that labor has on project execution. This research mainly focuses on the study of HR and its components to reach a deeper understanding of HR's impact on the competitiveness of construction companies. After defining the most relevant variables, an interrelationships model was proposed with the Partial Least Square (PLS) technique. These HR variables impact the competitiveness variables: cost, profitability, time, quality, staff retention, and Health and safety. The PLS (Partial Least Square) analyses met the evaluation criteria using the structural model, confirming its viability. It was found that there are three essential variables related to competitiveness: (i) leadership, (ii) values, and (iii) incentives and rewards.
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Sistema de almacenamiento energético con supercapacitores basado en un convertidor multinivel modular con auto-equilbrio embebido
(Fernado DávalosHernández, 2024)
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Rodrigo Cruz, Pedro Manuel
A medida que las fuentes de energía renovable interconectadas a la red aumentan, una solución viable para sostener la estabilidad de la red es mediante la implementación de Sistemas de Almacenamiento de Energía Distribuida (ESS, por sus siglas en inglés) a lo largo de la red. Para esta aplicación, los ESS deben ser capaces de manejar altas potencias en el rango de milisegundos a segundos, por lo que los Supercapacitores (SCs, por sus siglas en inglés) son dispositivos atractivos para cumplir con este requisito. El objetivo de la investigación es diseñar una topología de ESS que pueda ser expandible y escalable, evitando la complejidad de los sistemas actuales mediante el enfoque del Convertidor Multinivel Modular (MMC, por sus siglas en inglés). Por esta razón, un aspecto importante es mejorar los submódulos con capacidades de autobalance para acomodar tantos SCs como lo requiera la aplicación de la red. Los MMCs han sido ampliamente estudiados para aplicaciones de corriente continua de alta tensión, aunque son una tecnología costosa, los beneficios de implementarlos en proyectos a gran escala los convierten en una solución viable en contraste con las líneas de corriente alterna tradicionales, ya que proporcionan una forma más robusta y eficiente de transferir energía a largas distancias. Se ha realizado poca investigación en aplicaciones de MMC de baja tensión debido a la complejidad del controlador y los beneficios limitados en eficiencia, pero es un enfoque innovador agregar a cada Submódulo (SM) un dispositivo de almacenamiento de energía para crear un ESS. El ESS resultante puede escalar más rápidamente, ya que es posible simplemente agregar más SMs al sistema en serie para aumentar el voltaje o en paralelo para aumentar la potencia. Además, con la capacidad añadida de autobalance en los SCs, se puede diseñar un ESS robusto en comparación con los tradicionales, que requieren etapas de potencia independientes para lograr el sistema de balanceo, el convertidor CC/CC y el inversor CC/CA. Este trabajo de investigación cubre en detalle la metodología de diseño del MMC propuesto, las simulaciones que validan la propuesta y la operación de interconexión a la red, una metodología de optimización para analizar la eficiencia y mejorarla, y finalmente dos prototipos utilizados para validar el ESS basado en MMC propuesto. El primer prototipo a escala de laboratorio valida la operación del ESS basado en MMC, y el segundo prototipo valida las mejoras de eficiencia realizadas según la metodología de optimización, logrando alrededor de ~93% de eficiencia para un ESS basado en MMC de baja tensión completo de 220VAC y 16kW. En línea con la misión del Centro de Energía y Tecnología de Skoltech y la Facultad de Ingeniería de la Universidad Panamericana, esta investigación en conversión de energía puede proporcionar un convertidor ESS basado en MMC eficiente y puede ser utilizado para mejorar las capacidades de control de frecuencia de la red. Para concluir, se realizó una contribución relevante al campo de los MMCs de baja tensión con este trabajo de investigación de doctorado.
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Stochastic optimal control of an automotive supply chain using dynamic programming
(Carlos Eduardo López Landeros, 2025)
López Landeros, Carlos Eduardo
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Valenzuela González, Ricardo
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Olivares Benítez, Elías
La cadena de suministro automotriz es una de las más dinámicas y grandes a nivel mundial. Ante los diversos desafíos de suministro, producción y transporte que enfrenta, los socios de esta cadena necesitan coordinar sus operaciones para lograr eficiencia, robustez y confiabilidad. Esta coordinación es posible en estado transitorio y en ambientes con incertidumbre usando teoría de control. En tal virtud, en este trabajo se propuso un modelo de control óptimo estocástico para una cadena de suministro automotriz multi-producto de cinco eslabones operando bajo una estrategia push-pull, con el objetivo de minimizar el costo total de operación en un horizonte de tiempo definido. El modelo consideró restricciones de capacidad, operaciones de mezcla de partes, requerimientos de ensamblaje, tasas variables de suministro y de producción-inventario. Se asumió que la demanda de automóviles sigue una distribución normal, con costos unitarios de materias prima fluctuando como movimiento geométrico Browniano y niveles de disponibilidad de piezas variables comportándose como procesos de Itô. La dinámica se modeló como un balance de entradas y salidas en los nodos del sistema mediante ecuaciones diferenciales ordinarias. La solución del modelo propuesto se obtuvo con la adaptación y mejora de un algoritmo numérico de control óptimo basado en Programación Dinámica con el cual se determinaron los niveles óptimos de producción-inventario para cada socio de la cadena, impulsados por las tasas de adquisición de materia prima entrante. Se compararon diferentes configuraciones deterministas y estocásticas del modelo y los hallazgos proporcionaron información útil para los gerentes en las áreas de producción, inventario y transporte. Estos resultados son evidencia de los beneficios que representa modelar la cadena de suministro desde una perspectiva de control óptimo estocástico para la operación coordinada de sistemas industriales.

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