Publicações - engenharias
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Bráulio Farnese de Paula Lana;
Mônica Beatriz Kolicheski;
Arno Paulo Schmitz;
Alvaro Luiz Mathias;
GONTARSKI, CARLOS ALBERTO UBIRAJARA
Palavra-chave:
Cleaner Production;
solid waste;
solid waste minimization;
Industry 4.0;
expert system
Áreas do conhecimento:
Outros;
Engenharias; Engenharia Química; Bioprocessos
resumo ...
(pt)
Industry 4.0 has expanded the alternatives to design more sustainable processes. Among the technologies of this industrial phase, IoT (Internet of Things) technology allows the linkage of devices that generate data at high volumes (big data), supporting the creation of Artificial Intelligence (AI) models to perform optimal operating standards to minimize waste in the production. By means of vision sensor and AI deployment, this study aimed to reduce the polybutylene plastic waste in an extrusion line of colored tubes, in which most of the waste is generated during the color transition. For that, a vision sensor that transfers the tube color in real-time was installed, which made it possible to set acceptance ranges for the standard colors of the tubes based on the elicitation of the operators' knowledge. These ranges allowed the setup of an expert system that warns the operator, by a light signal, the right time to start the production. The suggested technology demonstrated to be 11.47% more efficient in waste reduction in color transitions. It also allowed the identification of the requirements for the deployment of this technology in plastic extrusion, so it can promote overall waste reduction, which requires improvements in operation, standardization, and employee training.
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Braulio F. P. Lana;
Monica B. Kolicheski;
Arno Paulo Schmitz;
Alvaro luiz Mathias;
Carlos A. U. Gontarski
Revista Latino-Americana de Inovação e Engenharia de Produção,
v. 12,
n. 20,
p. 74-94,
2024
DOI
Home page
Palavra-chave:
Algoritmos;
Eficiência produtiva;
Inteligência Artificial
Áreas do conhecimento:
Engenharias; Engenharia do Produto; Processos de Trabalho
resumo ...
(pt)
Industry 4.0 has expanded the alternatives to design more sustainable processes. Among the technologies of this industrial phase, IoT (Internet of Things) technology allows the linkage of devices that generate data at high volumes (big data), supporting the creation of Artificial Intelligence (AI) models to perform optimal operating standards to minimize waste in the production. By means of vision sensor and AI deployment, this study aimed to reduce the polybutylene plastic waste in an extrusion line of colored tubes, in which most of the waste is generated during the color transition. For that, a vision sensor that transfers the tube color in real-time was installed, which made it possible to set acceptance ranges for the standard colors of the tubes based on the elicitation of the operators' knowledge. These ranges allowed the setup of an expert system that warns the operator, by a light signal, the right time to start the production. The suggested technology demonstrated to be 11.47% more efficient in waste reduction in color transitions. It also allowed the identification of the requirements for the deployment of this technology in plastic extrusion, so it can promote overall waste reduction, which requires improvements in operation, standardization, and employee training.
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Guilherme Augusto Garcia Geronasso;
CABRAL, PALOMA SOUZA
Revista Unicrea,
v. 2,
n. 3,
p. 81-100-100,
2024
Palavra-chave:
Gerenciamento de Resíduos Sólidos
Áreas do conhecimento:
Engenharias; Tecnologia Química; Tratamentos e Aproveitamento de Rejeitos
resumo ...
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DAGA, ALISSON LUAN;
QUADROS, THIAGO DALGALO DE;
Marcelo Kaminski Lenzi
Palavra-chave:
controle de processos;
Controle Multivariavel
Áreas do conhecimento:
Engenharias; Engenharia Química; Bioprocessos
resumo ...
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FERRAZ, RAFAEL DA SILVA;
OLIVEIRA, SÓSTENES GUTEMBERGUE M;
Horacio Tertuliano dos Santos Filho;
DA SILVA, CLAUDIO BASTOS
Palavra-chave:
Electronic Circuits;
IoT;
Harvested Energy;
Magnetic Field;
performance;
Autonomy
Áreas do conhecimento:
Engenharias; Engenharia Elétrica; Telecomunicações;
Engenharias; Engenharia Elétrica; Circuitos Elétricos, Magnéticos e Eletrônicos
resumo ...
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Claudimir José Rebeyka;
Guilherme Matheus Sviech Pontarolo;
Marcelo Arceno;
Ravilson Antonio Chemin Filho;
LAJARIN, SÉRGIO FERNANDO
International Research Journal of Engineering and Technology (IRJET),
v. 11,
n. 09,
p. 130
2024
Home page
Palavra-chave:
Baja;
Projeto para manufatura;
simulação numérica
Áreas do conhecimento:
Engenharias; Engenharia Elétrica; Telecomunicações
resumo ...
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Marcelo Arceno;
Claudimir José Rebeyka;
Guilherme Matheus Sviec Pontarolo;
Ravilson Antonio Chemin Filho;
Sergio Fernando Lajarin
International Research Journal of Engineering and Technology (IRJET),
v. 11,
n. 09Sep2024,
p. 130-134,
2024
Home page
Áreas do conhecimento:
Engenharias; Engenharia Mecânica; Processos de Fabricação; Processos de Fabricação, Seleção Econômica
resumo ...
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PEREIRA, MARCO ALÉSIO FIQUEIREDO;
ALVES, AMANDA DE SOUZA;
Masato kobiyama
Palavra-chave:
junction angle
Áreas do conhecimento:
Ciências Exatas e da Terra; Geociências; Geografia Física; Geomorfologia;
Engenharias; Engenharia Civil; RECURSOS HÍDRICOS
resumo ...
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DIAS, ISABELA PEREIRA;
BARBIERI, SHAYLA FERNANDA;
DA COSTA AMARAL, SARAH;
Silveira, Joana L. M.
Palavra-chave:
Chemical modification;
Polyelectrolyte;
Calcium cross-linking
Áreas do conhecimento:
Ciências Biológicas; Química de Macromoléculas; Glicídeos;
Ciências Exatas e da Terra; Química; Físico-Química; Eletroquímica;
Engenharias; Engenharia Química; Tecnologia Química; Produtos Naturais
resumo ...
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DE SOUZA, DIEGO J.;
SANCHEZ, LEANDRO F.M.;
Juarez Hoppe Filho;
Marcelo Henrique Farias de Medeiros
Palavra-chave:
ataque por sulfatos;
durabilidade do concreto
Áreas do conhecimento:
Engenharias; Engenharia Civil; Inovação
resumo ...
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