PPG.EGPSA/ITEGAM

URI permanente desta comunidadehttps://rigalileo.itegam.org.br/handle/123456789/1

A comunidade dispõe da produção técnica e científica do Programa de Pós-graduação em Engenharia, Gestão de Processos, Sistema e Ambiental (PPG.EGPSA) do Instituto de Tecnologia e Educação Galileo da Amazônia (ITEGAM), fruto da atividade de pesquisa e desenvolvimento (P&D). É possível acessar os trabalhos de conclusão do programa de pós-graduação, artigos e livros vinculados a pesquisa, desenvolvimento, inovação e extensão.

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Aplicação da Lógica Fuzzy na Emissão de Notas Fiscais
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SOARES, Vera Alana Nobre; BRITO JUNIOR, Jorge de Almeida; ALENCAR, David Barbosa de; NASCIMENTO, Manoel Henrique Reis
Certificate issued by the Brazilian National Institute of Industrial Property (INPI) for the registration of the computer program entitled Application of Fuzzy Logic in Invoice Issuance. Developed in Python, the software aims to apply fuzzy logic principles to improve invoice analysis and issuance, providing greater precision, automation, and reliability to the process. The registration grants legal protection for 50 years under Law No. 9.609/1998, ensuring intellectual property and exploitation rights to ITEGAM and the authors.
Diagnóstico Difuso da Rentabilidade Empresarial: Modelo Mamdani Aplicado às Margens Bruta e Operacional
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) NASCIMENTO, Alessandra Souza; NASCIMENTO, Manoel Henrique Reis; ALMEIDA, Luiz Fernando Correia de; SANTOS, Eliton Smith dos
This article proposes and validates a Mamdani fuzzy-inference model to diagnose corporate profitability for Coelmatic Indústria de Componentes Eletrônicos Ltda., using 2024 income-statement data. Four input variables—General and Administrative Expenses (DGA), Tax Debt Ratio (DT), Financial Debt Ratio (DF) and Financial Return (RF)—were fuzzified into Low, Medium and High through trapezoidal membership functions calibrated on historical quartiles. An 81-rule IF–THEN base, generated by the Wang-Mendel algorithm and refined by domain experts, feeds the Mamdani core; centroid defuzzification yields the crisp score CompLucroO on a 0–30 scale. The model achieved a mean absolute error below 8 % against accounting ROE and a Kendall’s W of 0.85 versus analysts’ rankings, supporting the hypothesis that fuzzy logic captures performance nuances overlooked by crisp metrics. Limitations include single-year scope, subjective parameter tuning and exclusion of macroeconomic factors. Future work should extend the time series, explore type-2 or neuro-fuzzy systems, and incorporate ESG indicators.
Promoting Development and Environmental Awareness in Children with Disabilities: An Approach with Adapted Physical Education and Fuzzy Logic
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) CAMPOS, Paola Souto; LEITE, Jandecy Cabral
This study aimed to develop a fuzzy logic model to evaluate the impact of interventions in Adapted Physical Education and Environmental Education on the development of children with disabilities, covering physical, cognitive, and environmental awareness aspects. Scenario simulations mimicking real conditions and incorporating variables such as motor coordination and understanding of environmental concepts were implemented. The interventions were evaluated using fuzzy rules to measure the impacts on various development dimensions. Although the model was not applied practically with children, validation tests suggest its future applicability in practical studies. Results indicate that integrated and balanced interventions can effectively improve both physical and cognitive development. Fuzzy logic proved to be a robust tool for detailed progress evaluation, indicating that the developed model can significantly contribute to inclusive pedagogical practices and guide educational policies for children with disabilities while reinforcing sustainability in environmental education.
Implementação de práticas sustentáveis: avaliação fuzzy do desempenho e conscientização ambiental em crianças com deficiência
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) BEZERRA, Igor Felipe Oliveira; CAMPOS, Paola Souto
This study aimed to develop a fuzzy logic-based model to assess the impact of interventions in Adapted Physical Education and Environmental Education on the physical, cognitive, and environmental awareness development of children with disabilities. The need for inclusive educational strategies and accurate tools to capture individual progress underpins this work, which seeks to go beyond traditional assessment approaches. Using scenario simulations that replicate authentic conditions, the study incorporated variables such as motor coordination, strength, endurance, as well as attention and understanding of environmental concepts. Interventions were analyzed using fuzzy rules to assess the expected impacts in physical, cognitive, and environmental awareness dimensions. Although the model was not implemented in a real setting with children, its validation suggests future applicability in practical studies. The results indicate that well-integrated interventions, especially those that balance physical and cognitive development, can lead to substantial improvements. Fuzzy logic proved to be a valuable tool, allowing for detailed and gradual progress assessment. The proposed model is a significant addition to inclusive pedagogical practices and can guide educational policies to better meet the needs of children with disabilities, emphasizing the importance of sustainable environmental education.
Desenvolvimento de um Dispositivo Inteligente de Monitoramento de Energia Elétrica Integrado à Plataforma SGE com Aplicação da Lógica Fuzzy para Tomada de Decisão na Gestão Energética da Indústria 4.0
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SANTOS JUNIOR, Hélio Andrade dos; ALENCAR, David Barbosa de; SANTOS, Eliton Smith dos; CAMPOS, Paola Souto; MORAES, Nadime Mustafa; SANCHES, Antônio Estanislau; LEITE, Jandecy Cabral
Efficient management of electrical energy in industrial environments is a crucial challenge, exacerbated by the continuous increase in consumption and frequent inefficiencies in resource utilization. In this context, Industry 4.0 and Smart Grids emerge as promising approaches, integrating advanced digital technologies to optimize energy production, distribution, and consumption. This study developed and validated a portable electrical energy monitoring device integrated into the SGE platform, applying fuzzy logic to support real-time decision-making. The device demonstrated the ability to conduct detailed analyses of energy consumption and efficiency, enhancing the accuracy in detecting losses and critical inefficiency points.
Aplicação de Controle Fuzzy em Microgrids Solares como Auxílio na Mitigação de Interrupções em Comunidades Isoladas no Amazonas à Portaria Nº 140/2022
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SILVA NETO, Oswaldo Wanderley da; ALENCAR, David Barbosa de; SANTOS, Eliton Smith dos; BRITO JÚNIOR, Jorge de Almeida; SANCHES, Antonio Estanislau; LEITE, Jandecy Cabral
Isolated communities in the Amazon face significant challenges in accessing reliable energy due to logistical difficulties and lack of infrastructure. Photovoltaic microgrids emerge as a viable alternative but suffer from instability and frequent interruptions caused by environmental variability. This study investigates the implementation of fuzzy control in these systems to mitigate supply failures and improve operational efficiency, in compliance with INMETRO's Portaria No. 140/2022. The results show that fuzzy control is a promising solution to enhance the reliability and sustainability of energy in isolated communities.
Aplicação da lógica Fuzzy na emissão de notas fiscais em processos administrativos na Indústria Lean Office 4.0
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SOARES, Vera Alana Nobre; ALENCAR, David Barbosa de; SANTOS, Eliton Smith dos; CAMPOS, Paola Souto; MORAES, Nadime Mustafa; LEITE, Jandecy Cabral
Industry 4.0 has brought the need to integrate advanced technologies to improve the efficiency and agility of administrative processes. This study proposes the application of fuzzy logic to optimize the issuance of invoices, a critical process that faces challenges such as manual errors, delays, and high costs. A fuzzy model was developed that identifies key variables, applies inference rules, and tests the solution in a real environment with operational data. The results indicate a significant reduction in errors and processing times, in addition to gains in tax compliance and customer satisfaction.
Fuzzy Modeling to Define Corrosivity Potential in Oil Pipelines
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2023) SANTOS, Ivair Rafael Costa do NASCIMENTO, Manoel Henrique Reis ALENCAR, David Barbosa de AZEVEDO, Manoel S. Santos SANCHES, Antônio Estanislau; LEITE, Jandecy Cabral
In this work, a Fuzzy logic model was developed using the Fuzzy Logic Toolbox™ of the MATLAB® software to monitor the corrosivity potential in oil pipelines, where corrosion mechanisms are predominantly microbiological. Using operational parameters, the model presents itself as an alternative to conventional monitoring methods, allowing the estimation of corrosion rates and, therefore, the corrosivity potential. The model was applied to an oil pipeline, and its results were compared with conventional monitoring methods. The analysis concluded that the model can be effectively used as a monitoring method for pipelines with predominant microbiological corrosion, supporting the integrity management of oil pipelines.
Application of Fuzzy Logic for Decision-Making in the Criteria for Allocation and Distribution of Industrial Costs
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2023) NOVO, Breno Tello NASCIMENTO, Manoel Henrique Reis; LEITE, Jandecy Cabral
Cost accounting plays a fundamental role in the correct allocation and distribution of industrial costs, helping companies determine the unit cost of products or services offered. This study proposes a classification model for decision-making based on Fuzzy Logic to diagnose production performance with a focus on optimizing industrial cost allocation. The methodology was developed in three phases: identification of economic and production indicators, modeling of the Fuzzy system, and experimentation of the proposed model. The Fuzzy system generated 576 inference rules for analysis, allowing the classification of product performance and guiding the choice of the best costing method. The results demonstrate that Fuzzy Logic can enhance decision-making and improve industrial profit margins.
Implementação do controle fuzzy em microgrids fotovoltaicos para a mitigação de interrupções energéticas em comunidades isoladas do Amazonas: conformidade com o regulamento técnico da qualidade do INMETRO (Portaria nº 140/2022)
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) SILVA NETO, Oswaldo Wanderley da; ALENCAR, David Barbosa de
Isolated communities in the Amazon region face significant challenges in accessing a reliable and continuous electricity supply due to logistical difficulties and the lack of infrastructure for electricity generation and distribution. As an alternative, photovoltaic microgrids emerge as a potential solution. However, these systems encounter issues such as instability and frequent interruptions due to environmental variability and the complexity of managing local energy resources. This dissertation investigates the implementation of fuzzy control in these photovoltaic microgrids, aiming to reduce energy supply interruptions and promote more efficient and sustainable energy delivery. The study aligns with INMETRO Ordinance No. 140/2022, which approves the Technical Quality Regulation and the Conformity Assessment Requirements for Equipment for Generation, Conditioning, and Storage of Electrical Energy in Photovoltaic Systems. It is set within the context of Industry 4.0, focusing on enhancing energy management. Fuzzy control, due to its ability to handle uncertainties and variabilities inherent in dynamic systems, is implemented to optimize microgrid operations by dynamically adjusting operational variables according to environmental conditions and local energy demand. The study also examines compliance with the guidelines established by INMETRO, demonstrating the technical feasibility and potential benefits of this approach, which include maximizing energy efficiency and the sustainability of deployed systems. The application of fuzzy control in photovoltaic microgrids proves to be a promising solution for addressing energy challenges in remote regions, contributing to sustainable socio-economic development in the Amazon.

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