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Sistema de visão para controlo de processo
| Name: | Description: | Size: | Format: | |
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| 7.09 MB | Adobe PDF |
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Abstract(s)
O presente documento descreve o trabalho efetuado no âmbito de controlo de processo
de fabrico de matéria prima para a indústria imobiliária, no Departamento Técnico da
IKEA Industry Portugal, integrando em simultâneo a unidade curricular de
Tese/Dissertação (TEDI), em Engenharia Eletrotécnica e de Computadores (MEEC), na
área de especialização em Sistemas Autónomos (SA), no Departamento de Engenharia
Eletrotécnica (DEE) do Instituto Superior de Engenharia do Porto (ISEP).
O controlo de processo de fabrico na indústria é uma mais valia para se obter produtos
finais de acordo com os parâmetros de fabrico. E em conformidade, surgiu o projeto de
controlo de processo durante uma das fases de fabrico de inúmeros produtos
semelhantes numa das linhas de produção do IKEA Industry no qual o objetivo consiste
em verificar com recurso a um sistema de visão se a aplicação de forma automatizada de
3 ou 5 ripas de madeira contraplacada numa placa de High Density Fiberboard (HDF)
cumpre os parâmetros de distância definidos para cada referência de fabrico.
Deste modo, a solução consiste numa estrutura de alumínio equipada com duas câmaras
de visão computacional da SICK Sensor Intelligence, uma câmara Ruler 3000 posicionada
no topo, uma câmara TriSpector 1000 posicionada na lateral, um componente de
integração sensorial programável SIM 1012 e um encoder em contacto com o
transportador da linha. A nível de desenvolvimento de algoritmo, este foi desenvolvido
no IDE SICK AppStudio utilizando a sua programação nativa LUA que comunica através de
comunicação TCP/IP com o autómato PLC OMRON onde é efetuado todo o controlo da
linha de produção.
Os resultados obtidos foram validados durante o funcionamento da linha de produção
com a presença do supervisor de linha e do departamento de controlo de processo, para
diferentes tipos de referências de fabrico, onde se verificou que o sistema de visão
cumpre os requisitos , apresentando uma precisão na ordem dos 0.3 a 0.5 mm sem que
este influencie o comportamento da linha a nível de produtividade. Após o término do desenvolvimento do sistema, foi feita uma validação de desempenho periódica com o
supervisor de linha, com a qual se concluiu que o sistema tem o comportamento
desejado.
The present document describes the work carried out in the scope of manufacturing process control of raw materials for the real estate industry, in the Technical Department of IKEA Industry Portugal, simultaneously integrating the curricular unit Thesis/Dissertation (TEDI) in Electrical and Computer Engineering (MEEC), specializing in Autonomous Systems (SA), in the Electrical Engineering Department (DEE) of the Instituto Superior de Engenharia do Porto (ISEP). Manufacturing process control in the industry is an asset to obtain final products according to manufacturing parameters. Accordingly, the manufacturing process control project emerged during one of the phases of manufacturing numerous similar products on one of the IKEA Industry production lines. The objective is to verify, using a vision system, whether the automated application of 3 or 5 slats of plywood on a High Density Fiberboard (HDF) board complies with the defined distance parameters for each manufacturing reference. The solution consists of an aluminum structure with two SICK Sensor Intelligence computer vision cameras, a Ruler 3000 camera positioned at the top, a TriSpector 1000 camera positioned on the side, a programmable sensory integration component SIM 1012, and an encoder in contact with the conveyor of the production line. Regarding algorithm development, it was carried out in the SICK AppStudio IDE using its native LUA programming that communicates via TCP/IP with the OMRON PLC automaton where all production line control is performed. The obtained results were validated during the production line operation with the presence of the line supervisor and the process control department, for different types of manufacturing references. It was verified that the vision system is viable with an accuracy in the range of 0.3 to 0.5 mm without influencing the line's productivity behavior. After the system development was completed, periodic performance validation was conducted with the line supervisor, concluding that the system behaves as intended.
The present document describes the work carried out in the scope of manufacturing process control of raw materials for the real estate industry, in the Technical Department of IKEA Industry Portugal, simultaneously integrating the curricular unit Thesis/Dissertation (TEDI) in Electrical and Computer Engineering (MEEC), specializing in Autonomous Systems (SA), in the Electrical Engineering Department (DEE) of the Instituto Superior de Engenharia do Porto (ISEP). Manufacturing process control in the industry is an asset to obtain final products according to manufacturing parameters. Accordingly, the manufacturing process control project emerged during one of the phases of manufacturing numerous similar products on one of the IKEA Industry production lines. The objective is to verify, using a vision system, whether the automated application of 3 or 5 slats of plywood on a High Density Fiberboard (HDF) board complies with the defined distance parameters for each manufacturing reference. The solution consists of an aluminum structure with two SICK Sensor Intelligence computer vision cameras, a Ruler 3000 camera positioned at the top, a TriSpector 1000 camera positioned on the side, a programmable sensory integration component SIM 1012, and an encoder in contact with the conveyor of the production line. Regarding algorithm development, it was carried out in the SICK AppStudio IDE using its native LUA programming that communicates via TCP/IP with the OMRON PLC automaton where all production line control is performed. The obtained results were validated during the production line operation with the presence of the line supervisor and the process control department, for different types of manufacturing references. It was verified that the vision system is viable with an accuracy in the range of 0.3 to 0.5 mm without influencing the line's productivity behavior. After the system development was completed, periodic performance validation was conducted with the line supervisor, concluding that the system behaves as intended.
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Keywords
SICK Ruler TriSpector AppStudio SICK LUA CX-Programmer TCP/IP
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Without CC licence