Ingeniería en Sistemas, Electrónica e Industrial

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    Automatización del sistema de documentación empresarial en el Laboratorio Neo-Fármaco
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Software, 2024-08) Allauca Cajamarca, Yadira Carolina; Fernández Peña, Félix Oscar
    Administrative processes, when carried out manually, can be challenging. In the pharmaceutical industry, accuracy is essential; thus, processes such as document management using conventional methods are prone to human error, inefficient in information retrieval, and risky in terms of data integrity. This regulated environment requires strict control of records to ensure traceability and transparency. Laboratorio Neo-Fármaco faces these challenges in its commitment to Good Manufacturing and Documentation Practices. Currently, the manual process causes repetition of document codes and delays, jeopardizing the integrity of information due to possible uncontrolled alterations, and consuming a lot of time in validation. To address these problems, a web-based document management system is implemented. The research line involved in this work is Information Technology and Control Systems. The project begins with information gathering through technical interviews with all process owners to understand their needs. Subsequently, a requirements analysis is performed using the ISO/IEC/IEEE 29148:2018 standard. For the design and implementation, tools selected from comparative tables are used. Finally, system testing involves validating compliance with the defined requirements, conducting a survey to measure usability with the SUS, and culminating in a questionnaire where users expressed their perceptions of operational efficiency with the new software in document management.
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    Validación de ensayos por ruido e iluminación laboral según la Norma ISO17025:2017 para la empresa Presegman
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Carrera de Ingeniería Industrial, 2023-03) Freire Cobo, Ingrid Paola; Morales Perrazo, Luis Alberto
    PRESEGMAN provides advisory and training services in the field of Safety and Industrial Hygiene, the main problem is that it lacks the metrological process of measurements and does not have the standardization and validation of physical tests, therefore, this research aims to obtain noise tests. and lighting under ISO17025:2017 guidelines, for its accreditation and to demonstrate that its professional services are technically competent. The methodology applied was the technique of the structured interview to obtain information in relation to the offered tests, the survey of the technical requirements of ISO17025:2017 for the registration of non-conformities and the observation in the investigation of the reports and processes of the company to verify the level of compliance according to the ISO 17025:2017 standard, obtaining a 27% application. The main result obtained indicates that 67 requirements are mandatory, and for this, improvements were made such as the implementation of uncertainty calculations, linearity, control of environmental factors and standardization of the method, thus complying with 100% of the parameters required by this standard, in conclusion, it has been possible to present reliable results through technical reports and standardized procedures, completely improving the level of compliance.
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    Modelo matemático para predecir el grado de deserción de los estudiantes en el Instituto Superior Tecnológico Bolívar
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2023) Mejía Zamora, Edgar Patricio; Benalcázar Palacios, Marco Enrique
    Student desertion is an indicator of delay in education in any country in the world and this occurs with a greater impact in Ecuador. For this reason, it is important to take into account the research work that is presented through the following thesis. The purpose of this research is to predict the desertion of students from the Bolívar Higher Technological Institute in the city of Ambato. The Institute's archives show that 1,036 students were enrolled in the May-October 2022 semester in five majors. The calculated sample size is 280 surveys using a confidence level of 95% and a margin of error of 5%. The surveys were applied to two groups, the first to: 115 students who for any reason abandoned their studies in any semester but returned to continue their studies. A second group of 165 students who did not drop out at any time, used Google forms for the survey through multiple choice questions . Due to having an asymmetric dataset, it is necessary to balance the data so that the models to be used work correctly. In the present work, two algorithms are used: Support Vector Machines (SVM) and Feed-forward Artificial Neural Networks. When comparing the results obtained based on the F1 score, it was determined that the best algorithm was Feed-forward Artificial Neural Networks with an F-score value of 82.2% while in Support Vector Machines it yielded a value of 72.5 %.