Maestría Ingeniería
URI permanente para esta colecciónhttp://hdl.handle.net/11634/47664
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Tipo de ítem: Ítem , APLICACIÓN WEB PARA LA GESTIÓN INTEGRAL Y LA PREDICCIÓN DEL IMPACTO DEL RIESGO EN LOS PROCESOS DE NEGOCIO DE LAS PYMES DE TUNJA - BOYACÁ(Universidad Santo Tomás, 2026-02-05) Guio Camargo, Laura Sofia; Vargas Espitia, Yesica Daniela; Mendoza Moreno, Juan Francisco; Universidad Santo TomasThe effective application of business process management enables companies to meet their objectives and goals. In addition, process management facilitates the detection of risks that may affect an organization's performance. Risks, as scenarios of uncertainty, need to be managed in order to mitigate or eliminate their negative effects. This management is a systematic process that is applied to the company's life cycle to facilitate decision-making. In meetings held throughout this project and surveys conducted with SMEs in the city of Tunja and other municipalities and cities, various technological and organizational business risks were identified. In many cases, there is a lack of strategic objectives and no action is taken to identify and address risks. This lack of follow-up acts as a key target for the weakness in the foundations of institutions, as it is not customary to keep a historical record of the problems encountered in the processes, or the control is archaic in nature with no documentation. In other cases, documentation, risk matrices, and risk classification tables were available in Excel spreadsheets, but ultimately they were not comprehensive enough to manage risk as stipulated by institutions such as ICONTEC. With limited control over situations that entail risks, companies are exposed to a latent danger of economic and reputational losses and even the ultimate consequence of inadequate process management: business liquidation. Comprehensive risk management is an excellent strategy for avoiding business liquidation, which is very common among SMEs, especially in medium-sized and small cities. Tunja, Boyacá is a medium-sized city with interesting urban growth indicators. However, its business and industrial fabric is not growing at the same rate; although its SMEs are formally established, they lack adequate management of their internal processes. Therefore, it is necessary to design and implement a comprehensive risk management computer application that detects, diagnoses, and forecasts the risks inherent in business processes for subsequent treatment. This research project applies engineering methodologies, techniques, and strategies to develop this computer tool with two main components: risk detection and assessment, and risk impact prediction. During the construction of the tool, its impact was evaluated on a sample population of SMEs in the city of Tunja, using statistical instruments that allowed its reception to be analyzed. One of the scientific contributions of this research is the consolidation of a risk dataset that was constructed from the surveys conducted. This was the dataset used to train different machine learning models in order to choose the one that generated the highest accuracy. It should be noted that the data was supplemented with synthetic data generated using artificial intelligence techniques. This combination allowed the information base to be expanded and improved the accuracy of the selected predictive model.Tipo de ítem: Ítem , Planificación de Recursos Energéticos Distribuidos de una Red de Distribución Activa Desde una Perspectiva Resiliente(Universidad Santo Tomás, 2025-09-12) Melo Romero, Diego Felipe; Paternina Duran, Jose Luis; Vitola Oyaga, Jaime; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001652171; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000379204; https://scholar.google.com/citations?user=VEsFa94AAAAJ&hl=es&oi=ao; https://scholar.google.com/citations?user=dTnXldcAAAAJ&hl=es&oi=ao; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0002176743; https://orcid.org/0000-0001-8138-9588; https://orcid.org/0000-0003-4367-0592; https://orcid.org/0009-0001-0179-5568Context: The increase on the frequency of high impact with low probability of occurrence phenomena demands electric systems to implement energetic resilience solutions to avoid unexpected disruptions on the energy supply for final users. Methodology: This paper proposes a study to carry out the optimal planning of distributed energy resources in an active distribution network from a resilient perspective on the IEEE 34 system testing two critical scenarios on multiple failures and short and long durations. The investigation integrates electric modeling, an optimization problem and the use of Energy Not Supplied to mitigate vulnerabilities on critical infrastructure. A simulator was developed using Python with OpenDSS to model the IEEE 34 system, using multi-objective optimization on the selected distributed energy resources and the optimization method SLSQP and the selection of critic windows using the following criteria: maximum demand, minimum solar generation and critical combination. Results: Two high impact with low probability of occurrence scenarios were simulated: The first one during 6 hours and the second one during 120 hours resulting in the calculation of costs (USD) and Energy Not Supplied (kWh) where the main results show that the designed methodology makes the system able to face every scenario, as well as proving that planning distributed energy resources decreases the costs on the selected system during long durations. Conclusions: The study demonstrates that resilient solutions demand extensive battery energy storage, the selection of critical windows reduces more Energy Not Supplied than using windows with demand peaks only. The developed code shows a quantitative standard to prioritize investments on microgrids facing high impact low probability phenomena, balancing resilience costs.Tipo de ítem: Ítem , Incidencia de la variación de peso en bolsas de leche en envasadoras asépticas ocasionado por sellado servo asistido FESTO(Universidad Santo Tomás, 2024-04-24) Reyes Pino, Said Ricardo; Pardo Beainy, Camilo Ernesto; Chaparro Becerra, William FabianThe objective of this work was to determine the cause of weight variation of up to 60g in milk bags in an aseptic packaging machine, in which variables that are directly related to the weight of the bags were analyzed, in which the determination was reached. The cause is the horizontal sealing with Festo servomotors, the drive and synchronization generated by the communication between the PLC and the servomotor controller, since this system was approved given the world-wide effects for the acquisition of technological equipment; As a result of the discovery and correction of the system, a variation of +/-3g was obtained in the packaging, which was in accordance with the quality standards, which was due to routine execution times and data packet sending times.Tipo de ítem: Ítem , Estrategia pedagógica gamificada para soportar el proceso de enseñanza/aprendizaje de la programación orientada a objetos.(Universidad Santo Tomás, 2023-10-03) Suarez Rojas, Angie Lorena; Gutierrez Lopez, Luz Elena; Universidad Santo TomasThe objective of this project is to design a methodological strategy for the teaching and learning of Object Oriented Programming (POO) in order to facilitate the understanding of basic concepts of the object-oriented paradigm in students studying the Systems Engineering degree at the Santo Tomás Sectional Tunja University. To do this, we use techniques that transfer the mechanics of video games to educational environments (gamification), this technique is based on a methodology that consists of the realization of a series of steps ranging from diagnosis, bibliographic review and selection or design of the video game, until the execution of this. This research is based on a case study of the Santo Tomás University, the period for execution of the research was one semester (six months)Tipo de ítem: Ítem , Aplicación de escritorio para mantenimiento predictivo de equipos industriales de refrigeración a través de machine learning.(Universidad Santo Tomás, 2023-06-27) Quiroga Niño, Jose Andres; Barrera Gomez, Marien Rocio; Alfonso Diaz, Andres Leonardo; Universidad Santo TomasDevelopment of a platform that captures and analyzes information according to machine learning algorithms, from operational parameters and maintenance routines of industrial air conditioning systems. Predicting the occurrence of refrigerant gas leaks, by analyzing operational deviations.