Desarrollo de un sistema de reconocimiento para piezas faltantes en moldes en la industria de alimentos mediante el procesamiento de imágenes con matlab

The chocolate industry transforms cocoa production into finished products that are then exported. During production there is a risk of moulds breaking as mechanical parts of the equipment that cause moulds to deteriorate are involved in the manufacturing process, the probability of a piece of mould falling into a tablet and reaching a final consumer is high, which can generate legal penalties and economic losses for the company by creating a risk for the consumer, to reduce this, the present project makes an analysis of the variables involved in the chocolate injection process in the line super cavemil 800 and implements a system of image capture of the molds that make up the production machine and through the Matlab googlenet neural network image processing allows the recognition of missing parts in the molds can thus alert the operator of the machine the presence of an anomaly in them activating an alert protocol for production.

• Autores: Buitrago Lopez, Daniel Camilo
• Tipo de recurso: Trabajo de grado de pregrado
• Fecha de publicación: 2022
• Institución: Universidad Antonio Nariño
• Repositorio: Repositorio UAN
• Idioma: spa
• OAI Identifier: oai:repositorio.uan.edu.co:123456789/7261
• Acceso en línea: http://repositorio.uan.edu.co/handle/123456789/7261
• Palabra clave: Procesamiento de imágenes,; chocolate,; Deep learning,; súper cavemil 800,; Molde roto,; reconocimiento de patrones,; Googlenet.; Image processing,; chocolate,; deep learning,; super cavemil 800,; broken mold,; pattern recognition,; Googlenet
• Rights: openAccess
• License: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)