Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.12394/17336
Title: | Design of a machine for the production of advanced fabrics |
Other Titles: | Diseño de una máquina para la producción de tejidos avanzados |
Authors: | Meza Torres, Raul Oswaldo Hinostroza Flores, Anthony Jesus Soto Otivo, Luis Enrique Chamorro Quijano, Sario Angel Quispe Cabana, Roberto Belarmino |
metadata.dc.contributor.advisor: | Quispe Cabana, Roberto Belarmino |
Keywords: | Industria textil Textile industry Fibras textiles Textile fibers Automatización industrial Industrial automation Máquinas Machines |
Publisher: | Universidad Continental. |
Issue Date: | 2025 |
metadata.dc.date.available: | 19-May-2025 |
Citation: | Meza, R., Hinostroza, A., Soto, L., et al. (2025). Design of a machine for the production of advanced fabrics [Tesis de licenciatura, Universidad Continental]. Repositorio Institucional Continental. https://repositorio.continental.edu.pe/handle/20.500.12394/17336 |
metadata.dc.identifier.doi: | 10.1109/UEMCON62879.2024.10754768 |
Abstract: | Abstract — In this project, a design for an automated mechanism is presented for implementation in textile manufacturing processes, where an integrated system for textile fiber recognition based on artificial intelligence (AI) was added. The mechanical design of the machine was studied in terms of force, providing a robust and efficient structure that supports the integration of sensors and cameras for real - time image capture of the processed fibers. Additionally, this design included a precise feeding system and a transport mechanism that ensured the stability and correct positioning of the fibers during analysis. In parallel, an AI model was implemented to identify and classify textile fibers based on their color characteristics. A simulated dataset was generated , where each type of fiber was represented by a specific color (red, green, blue, yellow), and a simple neural network was trained to recognize these color patterns. The model was optimized to achieve high accuracy in fiber classification and was subsequen tly evaluated with a test set. The system also included a visualization functionality that allowed the recognized fiber color to be displayed along with its classification, providing visual validation of the process. This comprehensive approach, combining advanced mechanical design with AI, proved effective in improving the accuracy and efficiency of automatic textile fiber identification, significantly contributing to the optimization of production processes in the textile industry. |
Extension: | 9 páginas. |
metadata.dc.rights.accessRights: | Acceso abierto |
metadata.dc.source: | Universidad Continental Repositorio Institucional - Continental |
Appears in Collections: | Tesis |
Files in This Item:
File | Description | Size | Format | |
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IV_FIN_111_TE_Meza_Hinostroza_Soto_Chamorro_Quispe_2025.pdf | Meza Torres, Raul Oswaldo; Hinostroza Flores, Anthony Jesus; Soto Otivo, Luis Enrique; Chamorro Quijano, Sario Angel; Quispe Cabana, Roberto Berlarmino | 1.23 MB | Adobe PDF | View/Open |
Informe_Turnitin.pdf Restricted Access | Informe de Turnitin | 2.21 MB | Adobe PDF | View/Open Request a copy |
IV_FIN_111_Autorización_2025.pdf Restricted Access | Autorización | 154.4 kB | Adobe PDF | View/Open Request a copy |
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