Ingeniería en Sistemas, Electrónica e Industrial

URI permanente para esta comunidadhttp://repositorio.uta.edu.ec/handle/123456789/1

Examinar

Filtros

20261

Ajustes

Autor/a: search.filters.author.Lizano Muñoz, Alex SantiagoTema: search.filters.subject.TRAZABILIDAD

Resultados de la búsqueda

Mostrando 1 - 1 de 1
  • Miniatura
    Item type:Ítem,
    Sistema para el registro y control de procesos de abastecimiento en Ciauto
    (Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas Electrónica e Industrial. Carrera de Software, 2026-07-03)
    Lizano Muñoz, Alex Santiago
    ;
    Chicaiza Castillo, Dennis Vinicio
    ;
    Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas Electrónica e Industrial. Carrera de Software
    This project proposes the development of a system for the registration and control of processes at CIAUTO Cía. Ltda. The need arose from difficulties identified at the supply station, responsible for unloading and assigning vehicle lots, where the use of physical records and manual transcription of information resulted in duplication of tasks, an excessive administrative burden, and risks associated with data dispersion, hindering the availability and traceability of information. The methodology combined applied and field research, adopting a qualitative approach through interviews and a quantitative approach through a staff survey for subsequent analysis. BPMN diagrams and risk matrices were also used to diagnose and model processes. To address this problem, the technological solution was built using a stack composed of PostgreSQL, ASP.NET Core, and Angular, based on the principles of Clean Architecture and the CQRS pattern. The system centralized information, digitized activity logs, and automated form generation. It included a control panel for viewing key indicators such as container status, opening progress, tracking of new developments, supply progress, and operator performance, thus optimizing decision-making. As a result, the system’s implementation reduced processing times by 57,04 percent in operations and 83,1 percent in administration compared to the manual model, achieving a reduction in human error and unnecessary administrative burden.