Machine learning for the identification and classification of pieces in industrial manufacturing
In the world of industry, there is an increasing demand for machines, maybe not more sophisticated but more intelligent, capable of automating as many functions as possible, because the more tasks a machine can do, the more time for other things a human has. One possibility of increasing a machine’s...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/414900 |
| Acceso en línea: | https://hdl.handle.net/2117/414900 |
| Access Level: | acceso abierto |
| Palabra clave: | Neural networks (Computer science) Machine learning Computer network protocols Xarxes neuronals (Informàtica) Aprenentatge automàtic Protocols de xarxes d'ordinadors Àrees temàtiques de la UPC::Enginyeria electrònica Àrees temàtiques de la UPC::Informàtica |
| Sumario: | In the world of industry, there is an increasing demand for machines, maybe not more sophisticated but more intelligent, capable of automating as many functions as possible, because the more tasks a machine can do, the more time for other things a human has. One possibility of increasing a machine’s intelligence is the addition of new technologies like Machine Learning and IoT. Using as an example a piece classification problem, in this master's thesis, convolutional neural networks (CNN) models have been designed for the identification and classification of images and the transmission of its result to an industrial machine. Different systems for sending data to an industrial machine have been planned and created through the use of communication protocols such as Modbus TCP, OPC UA or MQTT. The Python programming language has been used with tools such as communication libraries for the aforementioned protocols and the Machine Learning development framework Tensorflow. At the end of this work, convolutional neural network model that identified and classified parts was created, and this information could be sent to an industrial machine that has one of the communication protocols named before. |
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