Modelo sistêmico para tratamento de dados no contexto da manutenção de equipamentos agrícolas em uma usina de cana-de-açúcar como apoio à implantação de sistemas de agricultura 4.0

• Ano de defesa: 2023
• Autor(a) principal: Iaksch, Jaqueline Sebastiany
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Curitiba; Brasil; Programa de Pós-Graduação em Engenharia Mecânica e de Materiais; UTFPR
• Palavras-chave em Português: Agricultura; Inovações agrícolas; Indústria 4.0; Processo decisório; Linguagem de Modelagem de Sistemas (Ciência da Computação); Inteligência competitiva (Administração); Equipamento agrícola - Manutenção e reparos; Internet das coisas; Sistemas agrícolas; Agriculture; Agricultural innovations; Industry 4.0; Decision making; Systems Modeling Language (Computer science); Business intelligence; Farm equipment - Maintenance and repair; Internet of things; Agricultural systems; CNPQ::ENGENHARIAS::ENGENHARIA MECANICA; Engenharia Mecânica
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/31536

Agriculture is facing increasing challenges due to several factors, such as population growth and climate change. Ways have been sought to improve profitability and agricultural efficiency through decision-making and better management control based on information and knowledge generated on the farm in its specific context. Technologies and innovative solutions have been applied as an alternative for collecting and processing this information with the arrival of the só-called fourth industrial revolution, which is generated by systems, equipment, markets, and agents involved in agricultural production. Transforming this data collected in the field into valuable data that supports better decision-making is essential. This work initially developed a model to provide a strategic vision of Agriculture 4.0 To support decision-making at a strategic, tactical, and operational level. Afterward, a systemic model was built that represents all the information along a generic agricultural scenario, allowing the support of tactical decisions related to Farms 4.0. Finally, an information model was developed with the objective of selecting and interpreting data originating from sensors present in agricultural implements, allowing them to assist in operational decision-making about the need for equipment maintenance in a predictive way. This work follows the Design Science Research (DSR) methodology, which aims to develop knowledge through solving real-world problems. This work is divided into six stages: (i) Identification of the problem and motivation; (ii) Definition of the objectives of the Solution; (iii) Solution design and development; (iv) Demonstration of the Solution; (v) Solution Evaluation; and, (vi) Communication of results. The Solution proposed in this research was applied and evaluated in the context of a partner agricultural machinery company in the scenario of sugar cane plantations. It enabled auxiliary decision-making regarding the maintenance of fuel filters for sugarcane harvesters.