Bibliographic citations
Sánchez, A., Roncalla, V. (2021). Sistema de diagnóstico de la calidad de piezas terminadas en una empresa procesadora de melamina mediante el procesamiento de imágenes aplicando técnicas y herramientas de deep learning [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/659115
Sánchez, A., Roncalla, V. Sistema de diagnóstico de la calidad de piezas terminadas en una empresa procesadora de melamina mediante el procesamiento de imágenes aplicando técnicas y herramientas de deep learning [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2021. http://hdl.handle.net/10757/659115
@misc{renati/398606,
title = "Sistema de diagnóstico de la calidad de piezas terminadas en una empresa procesadora de melamina mediante el procesamiento de imágenes aplicando técnicas y herramientas de deep learning",
author = "Roncalla Viena, Victor Antonio",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2021"
}
This thesis work proposes the design of a diagnosis system for the quality of melamine parts that through image processing and the application of deep learning techniques and tools will considerably improve the quality control process of a melamine manufacturing company. To achieve the expected result, a set of activities was performed including primarily project planning, business analysis and development of the solution proposal. Project planning is based on the practices from PMBOK® Guide, 6th edition, and includes the development of a series of plans that allows the management of different aspects of the project such as scope, schedule, costs, risks, communications, among others. On the other hand, to analyze the company's current situation, the Zachman framework was used as a reference allowing for analysis of the organization's business processes from different perspectives and identification of the obstacles that each of the processes face and those that are sought to be corrected with this proposed solution. Finally, to prepare the proposed solution, functional, non-functional and restrictions drivers were identified and prioritized. Design decisions are made on these drivers and documented using the C4 model diagrams.
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