Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Design and evaluation of heat exchangers for cooling thermoelectricdevices using additive manufacturing(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-11) Gonzáles Garibay, Ángel Bernardo; Rodríguez González, Ciro Ángel; emipsanchez; Cedeño Viveros, Luis Daniel; School of Engineering and Sciences; Campus Monterrey; Martínez López José IsraelThermoelectric modules is a relatively new technology for air conditioning systems en abled by solid state semiconductor base, with major challenges in implementation such as efficiency and high implementation costs. This thesis focuses on the design and manufactureof heat exchangers (HXs)generated using additive manufacturing (AM) that take advantage of the use of free form geometries impossible to manufacture using conventional technologies. Specifically, tryply periodic minimal surface (TPMS) based structures, were tested. For the assessment, diverse gyroid designs with stretched axes were compared against a standard (not stretched) design and a traditional extruded flat fins heat exchanger. Computational fluid dy namics (CFD) simulations and experimental testing were conducted using a custom designed wind tunnel to characterize the temperature drop for these designs. Experimental data suggest that the charactersic high surface area-to-volume ratio of standard gyroids provides a limited performance compared to the stretched configuration. A stretched 4-row gyroid demonstrated the best temperature gradient of 9.21◦C, while the regular gyroid and the stretched 1-row gyroid performed the worst, with gradients of 6.44◦C and 6.05◦C, respectively. However, the convective heat transfer coefficient for the stretched 4-row gyroid was 188.41 W/m2 · K, lower than that of the extruded flat fins design, which was 197.18 W/m2 · K. This indicates that, although the stretched 4-row gyroid design exhibited the most efficient heat absorption, resulting in a significant improvement in the thermoelectric assembly’s efficiency, it still has room for optimization to enhance its convective efficiency. Such improvements could fur ther boost the overall performance of thermoelectric modules. This underscores the potential of optimized complex geometries to significantly enhance both the thermal and overall effi ciency of thermoelectric systems and opens the possibilities to see additive manufactured heat exchangers as feasible for enhancing thermoelectric modules for air conditioning systems.
- Desempeño de pastas y morteros base cemento portland compuesto con adiciones de relleno inerte de caliza(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-11) Méndez Páramo, Rafael Alfredo; Torres Acosta, Andrés Antonio; emimmayorquin; Crespo Sánchez, Saúl Enrique; Anaya Díaz, Miguel; Escuela de Ingeniería y Ciencias; Campus Monterrey; Herrera Soto, Eduardo SadótEsta tesis evalúa el desempeño que tienen las pastas y morteros a base de cemento portland compuesto cuando la adición es relleno inerte de caliza (RIC). Se analizaron 6 tipos de cemento. Uno de los seis cementos fue del tipo cemento portland ordinario (CPO) que se utilizó como control para ver el desempeño del cemento portland compuesto (CPC). Primeramente, se caracterizaron los polvos de éstos con base a tres parámetros (densidad, pérdida por ignición y finura). Después se fabricaron pastas con los mismos cementos para evaluar sus parámetros físicos (cantidad de agua para consistencia normal, tiempos de fraguado y la coordenada L*). Finalmente se fabricaron morteros con los mismos para evaluarlos mecánica, física y químicamente (contenido de agua para fluidez normal, resistencia a la compresión, resistividad eléctrica, y profundidad de carbonatación). Los morteros se evaluaron a los 3, 28, 56 y 90 días de curado. Dos series de especímenes se curaron por 28 días y después se colocaron a la intemperie para determinar el efecto del medio ambiente durante 150 y 335 días. Los resultados mostraron que a mayor RIC tenga un cemento, este tendrá densidades más bajas, necesita mayor cantidad de agua para alcanzar consistencia normal en pastas y fluidez normal en morteros. En pastas de cemento se observó que a mayor es el contenido del RIC, menores serán los tiempos de fraguado inicial y final, lo que implica que la caliza endurece más rápido la pasta de cemento. Se determinó que las pastas de cemento con mayor RIC alcanzaron mayores valores de la coordenada L*, lo que implica que a mayor RIC mayor la blancura de la pasta de cemento. Los resultados obtenidos con las mezclas de mortero demostraron que a mayor es el contenido de RIC, su resistencia es mayor a edades tempranas, sin embargo, a edades mayores esta resistencia se queda estanca y los morteros fabricados con bajos contenidos de RIC, aumentan su resistencia con la edad. No se encontró una tendencia marcada en los valores de resistividad eléctrica de los morteros evaluados en función del contenido de RIC. Para los morteros que se expusieron al ambiente natural urbano entre 150 y 335 días, se observó un efecto en detrimento en las propiedades mecánicas de los mismos: a mayor contenido de RIC, mayor fue la reducción en la resistividad eléctrica y en la resistencia a la compresión. Esto se determinó por que la resistividad eléctrica se redujo entre un 10% y un 15% en los morteros fabricados con altos contenido de RIC. Por otro lado, la resistencia a la compresión se redujo entre un 15% y un 30% luego de los 335 días de exposición natural al ambiente de Querétaro. Ambas características físicas del material se vieron afectadas debido a que se encontraron fisuras en la superficie de los cubos, producto aparentemente de las reacciones químicas entre material y ambiente de exposición, que regularmente posee CO2 y S02. Finalmente, se comprobó que la prueba de pérdida por ignición ayuda a determinar indirectamente el contenido de RIC del cemento, para de esta manera reducir las posibles afectaciones que podrían generar a materiales base cemento Portland (lechadas, morteros y concretos) diseñándolos, dependiendo del uso y ambiente al que será sometido durante su vida de servicio.
- Impact of Industry 4.0 on Small and Medium Enterprises: Evaluation of Maturity Indices and Implementation Methodologies(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-11) Delgado González, Jessica; Román Flores, Armando; emimmayorquin; Cuan Urquizo, Enrique; School of Engineering and Sciences; Campus Monterrey; Vázquez Hurtado, CarlosThe digital transformation driven by Industry 4.0 technologies is reshaping global economic and business paradigms. Small and medium-sized enterprises (SMEs) in Mexico, which represent 99.8% of the country's economic units and contribute over 52% to its GDP, face significant barriers such as limited financial resources, technological gaps, and cultural resistance. These constraints, highlighted in recent studies, underscore the need for tailored tools to support their digitalization efforts. This thesis develops a digital maturity model specifically adapted to Mexican SMEs, integrating practical tools such as an assessment framework and a step-by-step action plan. The study begins by analyzing the theoretical foundations of Industry 4.0 and existing digital maturity models while addressing challenges unique to SMEs. Building on this foundation, the proposed model evaluates SMEs' current digital maturity and provides actionable recommendations through a simulation applied to a representative SME. The results demonstrate the model’s utility in identifying areas for improvement, fostering innovation, and enhancing competitiveness and sustainability in a globalized market. This work contributes academically by adapting global models to local contexts and practically by offering a replicable framework to bridge the digital divide in this critical economic sector.
- Analyzing VR and AR I4.0 technologies for industrial applications: A comparative study and selection approach development(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-11) Chavez Najera, Daniela Monserrat; Ahuett Garza, Horacio; emipsanchez; Urbina Coronado, Pedro Daniel; Orta Castañón, Pedro Antonio; School of Engineering and Sciences; Campus MonterreyIn recent years, the implementation of immersive technologies such as Virtual Reality (VR) and Augmented Reality (AR) for Industry 4.0 (I4.0) applications has increased considerably. These technologies enable the connection of virtual and real environments focusing on human centered manufacturing. A challenge when implementing immersive technologies in industrial tasks is the lack of clear paths to select the most appropriate technology for specific operations, and the nonexistence of metrics to evaluate the integration performance. Nonetheless, there are trends in the literature that offer insights to conduct the decision making process for selection between immersive technologies, ensuring the suitability of the application. Based on the decision criteria identified in the literature a decision making approach is developed. This thesis also presents the development workflow of three VR/AR applications implemented in Unity Engine for Meta Quest 3 and Hololens 2. These applications are evaluated using overall performance metrics and are analyzed using the proposed approach.
- Improving the design of multivariable milling tools combining machine learning techniques(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-05) Ramírez Hernández, Oscar Enrique; Olvera Trejo, Daniel; emipsanchez; Puma Araujo, Santiago Daniel; Martínez Romero, Oscar; School of Engineering and Sciences; Campus Monterrey; Fuentes Aguilar, Rita QuetziquelChatter in milling operations degrades surface quality, compromises dimensional accuracy, accelerates tool wear and may damage spindle components. One effective strategy to mitigate chatter while maintaining high productivity is the use of specialized milling tools, such as multivariable milling cutting tools (MMCT), designed with variable geometry in their pitch (𝜙) and helix (β) angles. However, identifying the combination of these angles remains challenging because of the absence of analytics models that link MMCT geometrical parameters with dynamic stability limits. This study proposes a novel approach that integrates analytical lobes calculation with machine learning to enhance tool design efficiency. We find optimal tool geometry (pitch and helix angles) and cutting conditions (spindle speed and axial depth) to maximize the Material Removal Rate (MRR) in milling of a single degree of freedom. Our approach employs a genetic algorithm (GA) combined with a pattern recognition neural network (NN) to predict whether specific parameter combinations will yield stable or unstable behavior. The Multilayer Feedforward Neural Network is trained using a database generated from simulation of a SDOF mathematical model of milling, a non-autonomous Delay Differential Equation. The solution to the DDE is approximated through the Enhanced Multistage Homotopy Perturbation Method (EMHPM). The database includes 23,606,700 observations, covering a catalog of 36,318 MMCT configurations and 650 cutting conditions (axial depth of cut and spindle speed) for each tool configuration. The NN training database uses an approach for handling variable cutting coefficients based on exponential fitting model to describe their variation. These coefficients were characterized at small radial immersion of 1.86 mm using cutting forces of five MMCTs with a diameter of 0.5 in. This approach accurately predicts cutting forces, achieving an NRMSE below 10% when compared with experimental signals. The trained NN estimates the stability of the milling process with an error of 3.3%. Additionally, the combined use of the NN and GA reduces computation time by 98% compared to the GA with EMHPM. The selection of five combinations of geometric parameters that maximize MRR in a range between 26% and 120%, compared to the MRR of a regular tool, which is 190,493 mm³/min, has been performed. The rate of increase in MRR depends on each of the five selected geometries (see Chapter 5). Moreover, without the proposed approach, identifying the improved geometry would require up to 25 days using an exhaustive search scheme, where a SLD is generated for 10,000 cutting conditions for every tool configuration.
- Modification of photosensitive resin with 0D and 2D nanoparticles towards printing scalability(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-05) Meza Diarte, Salvador Alejandro; Sustaita Narváez, Alan Osiris; Rodríguez Hernández, Gerardo; Segura Cárdenas, Emmanuel; Melo Máximo, Dulce Viridiana; School of Engineering and Sciences; Campus Monterrey; Iturbe Ek, JackelineComposite materials, recognized for their ability to synergize the properties of multiple constituents, have become indispensable in modern engineering and manufacturing. Polymer composites, a prominent category within this field, are particularly valued for their lightweight, cost-effective nature, and ease of processability. This study investigates the integration of composite materials with vat polymerization 3D printing, focusing on the development of advanced polymer-based nanocomposites with tailored functional properties, by modifying commercially available photosensitive resins through ultrasonic dispersion of 0D and 2D nanoparticles: silicon dioxide (SiO2) and organo-modified clay Cloisite 30B (C30B), respectively. The SiO2 nanoparticles were functionalized with alkyl silane groups CTMS and OTS to achieve hydrophobicity. Therefore, this work aims to enhance the hydrophobic and flame-resistant characteristics of 3D printed components. A practical experimental methodology for the resin modification by ultrasonic dispersion was developed. The incorporation of functionalized SiO2 achieved intrinsically hydrophobic 3D printed specimens, with contact angle of up to 133°. The incorporation of C30B increased significantly mechanical properties with respect to neat resin, obtaining an increase of 37% in Young’s modulus, 39% in elongation, and 0.95 MPa. It also increased combustion temperature by 12 °C in the formulation with 5% clay concentration. XRD and TEM results confirm a clay exfoliation was achieved after polymerization, and the mechanism was proposed. A Jacob’s cure depth working curve was developed for both modifications to determine their printing parameters as the first step towards printing scalability. UV-Vis analysis confirmed that both modifications preserved the printability of the resins, demonstrating the feasibility of fabricating high-performance nanocomposites using vat polymerization
- Desarrollo de un material compuesto basado en metal "arcilla metálica" para aplicaciones de manufactura aditiva en la fabricación de microdispositivos(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-03) López Solís, Sergio Jesús; Segura Cárdenas, Emmanuel; emimmayorquin; Ulloa Castillo, Nicolas Antonio; Melo Máximo, Dulce Viridiana; Montañez Rodríguez, Abraham; Escuela de Ingeniería y Ciencias; Campus MonterreyEstá investigación explora el desarrollo y la validación de un compuesto metálico llamado “arcilla metálica” mediante fabricación aditiva por extrusión. Su objetivo es identificar los parámetros clave para la composición del material, el proceso de fabricación y las condiciones de sinterización. El estudio analiza la formulación del compuesto metálico, la adaptación de una impresora 3D para la extrusión y los hallazgos experimentales sobre materiales como Inconel 718 y acero inoxidable 316L. Se estudian y prueban varias proporciones de agua, polvo metálico y aglutinante orgánico para lograr una extruibilidad óptima, y el análisis termogravimétrico y espectroscópico ayuda a comprender las propiedades térmicas. El trabajo también evalúa las optimizaciones de la impresión 3D, incluidos los ajustes de la impresora, los tamaños de las boquillas y las resoluciones de impresión, y examina la fabricación de microcanales con un enfoque en la precisión y los procesos de sinterización para minimizar la porosidad. El estudio concluye con información sobre cómo mejorar la calidad y la reproducibilidad de la impresión, lo que contribuye a la fabricación de microdispositivos de arcilla metálica.
- Environmental assessment of urban rivers through a dual lens approach: machine learning based water quality analysis and metagenomic characterization of contamination effects(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-03) Fernández del Castillo Barrón, Alberto; Gradilla Hernández, Misael Sebastián; emipsanchez; García González, Alejandro; Pacheco Moscoa, Adriana; Brown, Lee; Oscar Alejandro Aguilar Jiménez; School of Engineering and Sciences; Campus Monterrey; Senés Guerrero, CarolinaUrban rivers are critical ecosystems increasingly threatened by pollution. Effective water quality monitoring and contamination assessment are essential for informed management decisions. The Santiago River, a key hydrologic system in Mexico, has become one of the country’s most polluted rivers, posing significant ecological risks and public health concerns for nearby communities. This study underscores the urgent need for comprehensive environmental evaluation and enhanced monitoring approaches. Chapter one introduces the motivation behind monitoring water quality in highly polluted rivers, presenting the problem statement and contextual background of the Santiago River basin. It outlines the research question and provides an overview of the proposed dual-lens approach: combining water quality analysis via machine learning algorithms with metagenomic characterization of contamination effects. Key contributions of this work to the field are also highlighted. Chapter two reviews global monitoring strategies from highly polluted rivers, focusing on nine rivers across developed and developing countries to offer a comparative perspective on water quality management needs. In Chapter three, regression and classification machine learning models are developed to predict the Santiago River Water Quality Index (SR-WQI), designed as complementary tools to strengthen the current monitoring program. Chapter four analyzes the historical water quality patterns of the Santiago River to identify the most variable and representative data for training machine learning models. This chapter also reveals that redundant data can hinder model performance by leading to overfitting. Chapter five investigates spatial variations in the microbial composition of Santiago River sediments and examines correlations with water quality. Using high-throughput sequencing, potential microbial biomarkers were identified and impacts of physicochemical parameters and heavy metals on microbial communities were assessed. Finally, chapter five highlight the main findings of this thesis and covers some limitations, perspectives for future research and final remarks.
- View planning for three-dimensional environment reconstruction using the Next Best View method(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-03) Shain Ruvalcaba, Everardo; López Damian, Efraín; emipsanchez; Santana Díaz, Alfredo; López Damián, Efraín; School of Engineering and Sciences; Campus Ciudad de México; González Hernández, Hugo GustavoThis study was made with the purpose of understanding the impact of the objective functionand optimization methods on the Next Best View problem, which consists in finding the next position that the sensor or camera needs to take to scan an object or scenery in its totality. A simulated 5-Degree-of-Freedom mobile robot with a mounted simulated range sensor was used on a Virtual Reality Modeling Language environment, and the space discretization was made using a voxel map. For the objective function, two main factors were included: an area factor to make sure that the image taken by the sensor provides the best possible information, and a motion factor made up of distance and energy sub-factors to reduce the resources used by the robot, making multiple experiments on a laboratory scene to determine their best arrangement on the final objective function. Global optimization tasks such as a backstepping technique to escape local minima and a dynamic change in the objective function were implemented. The retrievement of the scene was made on an iterative process, with each iteration needing an optimization process for which three different methods were tested: Nelder-Mead, an Evolution Strategy, and Simulated Annealing. A set of experiments comparing the three methods in computational time and retrievement efficiency were made on three different environments with increasing difficulty to test their repeatability, with them being a laboratory model, a room with a cube and a pyramid inside it, and a study room with multiple furniture and windows.
- Advanced path tracking: a study on autonomous vehicle control against different scenarios(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-03) Castillo Sánchez, Juan Pablo; González Hernández, Hugo Gustavo; emipsanchez; Moreno Moreno, Jesús; School of Engineering and Sciences; Campus Ciudad de México; Reyes Avendaño, Jorge AntonioAutonomous vehicles have been progressively deployed around the world, bringing numerous challenges remaining in hand due to their intrinsically complex nature. Among them, one of the most critical issues is motion control since it determines the performance of autonomous driving against a wide range of scenarios. This research evaluates the performance of different path tracking control strategies under specific driving conditions and trajectories, along with the exploration of localization algorithms, a fundamental step preceding the motion control stage. The proposed control techniques were simulated based on a single-track 2-DOF vehicle model and then validated through indoor physical tests on a Quanser scaled mobile platform called QCar.
