Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12394/17336
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dc.contributor.advisorQuispe Cabana, Roberto Belarminoes_PE
dc.contributor.authorMeza Torres, Raul Oswaldoes_PE
dc.contributor.authorHinostroza Flores, Anthony Jesuses_PE
dc.contributor.authorSoto Otivo, Luis Enriquees_PE
dc.contributor.authorChamorro Quijano, Sario Angeles_PE
dc.contributor.authorQuispe Cabana, Roberto Belarminoes_PE
dc.date.accessioned2025-05-19T17:32:20Z-
dc.date.available2025-05-19T17:32:20Z-
dc.date.issued2025-
dc.identifier.citationMeza, 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/20.500.12394/17336es_PE
dc.identifier.urihttps://hdl.handle.net/20.500.12394/17336-
dc.description.abstractAbstract — 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.es_PE
dc.formatapplication/pdfes_PE
dc.format.extent9 páginas.es_PE
dc.language.isospaes_PE
dc.publisherUniversidad Continental.es_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/es_PE
dc.sourceUniversidad Continentales_PE
dc.sourceRepositorio Institucional - Continentales_PE
dc.subjectIndustria textiles_PE
dc.subjectTextile industryes_PE
dc.subjectFibras textileses_PE
dc.subjectTextile fiberses_PE
dc.subjectAutomatización industriales_PE
dc.subjectIndustrial automationes_PE
dc.subjectMáquinases_PE
dc.subjectMachineses_PE
dc.titleDesign of a machine for the production of advanced fabricses_PE
dc.title.alternativeDiseño de una máquina para la producción de tejidos avanzadoses_PE
dc.typeinfo:eu-repo/semantics/bachelorThesises_PE
dc.rights.licenseAttribution 4.0 International (CC BY 4.0)es_PE
dc.rights.accessRightsAcceso abiertoes_PE
dc.publisher.countryPEes_PE
thesis.degree.nameIngeniero Mecánicoes_PE
thesis.degree.grantorUniversidad Continental. Facultad de Ingeniería.es_PE
thesis.degree.disciplineIngeniería Mecánicaes_PE
thesis.degree.programPregrado presencial regulares_PE
dc.identifier.doi10.1109/UEMCON62879.2024.10754768-
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.03.00es_PE
renati.advisor.dni09612760-
renati.advisor.orcidhttps://orcid.org/0000-0002-0452-7825es_PE
renati.author.dni70783732-
renati.author.dni73032765-
renati.author.dni70287321-
renati.author.dni72721011-
renati.author.dni09612760-
renati.discipline713046es_PE
renati.levelhttps://purl.org/pe-repo/renati/level#tituloProfesionales_PE
renati.typehttps://purl.org/pe-repo/renati/type#tesises_PE
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_PE
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IV_FIN_111_TE_Meza_Hinostroza_Soto_Chamorro_Quispe_2025.pdfMeza Torres, Raul Oswaldo; Hinostroza Flores, Anthony Jesus; Soto Otivo, Luis Enrique; Chamorro Quijano, Sario Angel; Quispe Cabana, Roberto Berlarmino1.23 MBAdobe PDFView/Open
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