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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Projeto Multicritério de Filtros Harmônicos Passivos para Instalações Industriais Utilizando Técnicas de Inteligência Computacional - NSGA-II
(Instituto Nacional da Propriedade Industrial (INPI), 2013-05-29) SIQUEIRA JUNIOR, Paulo Oliveira; LEITE, Jandecy Cabral; http://lattes.cnpq.br/7279183940171317
This document describes a computer program registered under number BR512023001304-8, which implements a multi-criteria design of passive harmonic filters for industrial installations, using the NSGA-II algorithm (Non-dominated Sorting Genetic Algorithm II), a computational intelligence technique. The objective of the program is to optimize the performance of passive harmonic filters, ensuring greater efficiency in mitigating harmonic distortions in industrial electrical systems. The multi-criteria approach allows you to consider different aspects of performance simultaneously, resulting in balanced and efficient solutions. This program is relevant to engineers and technicians seeking to improve power quality in industrial environments. Program registration is valid for 50 years from January 1, 2024.
Different Deterministic Optimization Methods for Economic Load Dispatch, Switching Off Less Efficient Generators
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2017) LEITE, Jandecy Cabral; CAMPOS, Paola Souto
The Economic Load Dispatch (ELD) is one of the most important optimization and operational decision tasks in power systems. This study compares various deterministic mathematical optimization methods, including Lambda Iteration, Newton’s Method, and Quadratic Programming, to solve the ELD problem. The analysis considers both the traditional methodology and a proposed approach that includes turning off less efficient generators to reduce costs and improve system efficiency.
Multi-Objective Optimization Techniques to Solve the Economic Emission Load Dispatch Problem Using Various Heuristic and Metaheuristic Algorithms
(IntechOpen, 2018) NASCIMENTO, Manoel Henrique Reis; LEITE, Jandecy Cabral
The chapter addresses the economic emission load dispatch problem, focusing on minimizing emission levels and total generation cost in thermal power plants. Various multi-objective optimization techniques, including heuristic and metaheuristic algorithms such as Simulated Annealing, Ant Lion, Dragonfly, NSGA II, and Differential Evolution, are analyzed. The chapter also compares the effectiveness of these approaches through a case study applied to a thermal generation plant.
Maintenance Management with Application of Computational Intelligence Generating a Decision Support System for the Load Dispatch in Power Plants
(IntechOpen, 2019) LEITE, Jandecy Cabral; NASCIMENTO, Manoel Henrique Reis
This chapter proposes the development of a computational tool to support load dispatch decisions based on the operational conditions of motors and generators in thermal power plants. The tool uses a fuzzy system to classify failure probabilities, based on indicators such as lubricating oil analysis, vibration analysis, and thermography of power generation equipment. The goal is not only to monitor the equipment's condition but also to take corrective actions to maintain service reliability and quality, considering the operating conditions of the equipment.
Análise da dispersão dos indicadores de desempenho para a tomada de decisão entre duas ferramentas de modelagem fuzzy Analysis of the dispersion of performance indicators for decision making between two fuzzy modeling tools
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2020) SILVA, Ítalo Rodrigo Soares; SIQUEIRA JÚNIOR, Paulo Oliveira; PARENTE, Ricardo Silva; NASCIMENTO, Manoel Henrique Reis; ALENCAR, David Barbosa de; LEITE, Jandecy Cabral.; LEITE, Jandecy Cabral
Analyzing data processing methods and ensuring consistent results is hard work for scientists. The optimization of a process makes a difference regardless of the area being worked on. This research used a comparative method of dispersion analysis to evaluate the performance of two fuzzy modeling tools: the Fuzzylite library and the MatLab® Fuzzy Toolbox. The case study was conducted with the School Adventurers application, which uses the Fuzzylite library for fuzzy inferences. The results indicated that Fuzzylite showed superior performance in terms of dispersion of performance indicators.
Sistema fotovoltaico no aeroporto internacional de Manaus: Análise da viabilidade técnica, econômica e ambiental de implantação usando simulação computacional
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2020) FONTINELLE, Carlos Gomes; SILVA, Simone da
The study analyzes the feasibility of implementing a photovoltaic system at the Eduardo Gomes International Airport in Manaus. Two project proposals were developed, considering technical, economic, and environmental factors. Simulation software was used to validate numerical values, and the results indicated that the system's implementation is feasible in all analyzed aspects.
Uma Proposta Inovadora Utilizando Blockchain para a Gestão Financeira em Obras Públicas, Tendo como Base o Sistema Brasileiro
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2020) JÚNIOR, Paulo Oliveira Siqueira; CAMPOS, Paola Souto
The poor investment of funds in public works across different sectors in Brazil is evident due to the concentration of technologies and new methodologies, varying according to the current legislation in each state. This study proposes a blockchain-based methodology to increase confidence in financial data, enabling greater transparency, reliability, and public sector oversight. The blockchain network allows mirroring of revenues and expenses, making financial processes more secure and auditable.
Gestão de estoque como vantagem competitiva em uma confeitaria na cidade de Manaus-AM
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) BAIA, Karla Josiane de Lima; ALENCAR, David Barbosa de
This chapter addresses inventory management in a confectionery located in Manaus-AM, highlighting the importance of proper planning to minimize costs and maximize profits. The research used the BCG Matrix and Production Planning and Control (PPC) to evaluate the confectionery's product portfolio and implement management techniques that ensure efficiency in inventory management, avoiding waste and material shortages. As a result, the confectionery is expected to gain a competitive advantage, staying ahead of competitors and ensuring final customer satisfaction.
Uma Proposta Inovadora Utilizando Blockchain para a Gestão Financeira em Obras Públicas, Tendo como Base o Sistema Brasileiro
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) PARENTE, Ricardo Silva; NASCIMENTO, Manoel Henrique Reis
This chapter presents an innovative proposal for financial management in public works in Brazil using blockchain technology. The objective is to increase transparency and efficiency in the use of public resources, reducing the possibility of corruption and financial deviations. The proposal includes the creation of a blockchain-based system that securely and immutably records and monitors all financial transactions, allowing real-time audits. The study discusses the practical implications of implementing this technology in the public sector and proposes a model adapted to the Brazilian reality.
A Implantação do 5S em uma Confeitaria da Cidade de Manaus-AM, Utilizando Ferramentas da Qualidade
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) COELHO, Sarah Marjurye da Silva; ALENCAR, David Barbosa de
This chapter presents the implementation of the 5S program in a confectionery located in Manaus-AM, aiming to improve the organization, cleanliness, and efficiency of the work environment. Using quality tools such as the PDCA cycle and the 5W2H action plan, the study proposes a management model that seeks to reduce costs and increase productivity. The application of 5S proved to be effective in optimizing space and improving employee performance, resulting in a more organized and productive work environment.
BAYESIAN REGULARIZERS OF ARTIFICIAL NEURAL NETWORKS APPLIED TO THE RELIABILITY FORECAST OF INTERNAL COMBUSTION MACHINES IN THE SHORT-TERM
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) SILVA, Ítalo Rodrigo Soares; NASCIMENTO, Manoel Henrique Reis; FONSECA JÚNIOR, Milton; PARENTE, Ricardo Silva; SIQUEIRA JÚNIOR, Paulo Oliveira;; LEITE, Jandecy Cabral
This work proposes a computational model to predict the Reliability Key Performance Indicator (KPI) to identify how available equipment will be in a time span of 22 days. The methodology to be used will be based on analyzes and tests of artificial neural network (ANN) architectures using the Bayesian Regularizers training algorithm, alternating the transfer functions in the hidden layers to find the best state of convergence and the minimum Root Mean Square Error (RMSE) value calculated between the real and simulated outputs. According to the results obtained by the training, validation and test steps, the algorithm presented a RMSE rate of 0.0000104202 and a 99.9% correlation between the real and simulated values, thus the model is able to identify which machine will have the greatest efficiency and less efficiency within the defined time span.
Application of Automation and Computer Vision in Reducing Failures in the Production Process of Safety Belts
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) SOUZA, Kerlisson Silva de; SANTOS, Eliton Smith dos; ALENCAR, David Barbosa de; NASCIMENTO, Manoel Henrique Reis; SANTOS, Alyson de Jesus dos; LEITE, Jandecy Cabral
Product quality is one of the primary criteria considered by customers when choosing an item and an essential factor for companies to stand out in the competitive market. In the Manaus Industrial Hub (PIM), defect detection in the production of safety belts is a critical stage. This study proposes a solution based on artificial intelligence and computer vision to automate this inspection, ensuring greater efficiency and reliability. An algorithm was developed using Deep Learning (DL), achieving 100% accuracy in defect identification, representing a significant advancement for automated inspection.
Composting Model with the Reuse of Organic Waste in Rural Schools
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) SIMÕES, Natália Cristina Bezerra de Alencar; ALENCAR, David Barbosa de; BEZERRA, Alberto de Souza; NASCIMENTO, Manoel Henrique Reis; FERRO, Any Karoline Bezerra de Alencar; PINTO JÚNIOR, José Roberto Lira; LEITE, Jandecy Cabral
School institutions generate organic waste due to daily meal consumption. A sustainable alternative is the implementation of a composting model to reuse this waste, generating humus, which can serve as fertilizer for school gardens. This study proposes the implementation of a compost bin in a rural school in Manaus, addressing the development of a prototype, the creation of a guideline manual for compost management, and the implementation of the school garden system. The project aims to raise awareness among the school community about proper solid waste management and reuse, promoting environmental education and behavioral change.
Evaluation of Radiated Electromagnetic Immunity of the IoT LoRa Protocol
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) RIBEIRO, Jhonatan; SANTOS, Eliton Smith dos; ALENCAR, David Barbosa de; NASCIMENTO, Manoel Henrique Reis do; SANTOS, Alyson de Jesus dos; LEITE, Jandecy Cabral
With the advancement of Industry 4.0, industrial automation has transitioned to wireless networks, enhancing flexibility and efficiency. Technologies such as LoRaWAN are widely adopted due to their low power consumption and long-range communication capabilities. However, the increasing density of connected devices presents challenges related to electromagnetic interference (EMI), which can degrade network performance. This study evaluates the radiated electromagnetic immunity of the LoRa protocol, testing Heltec LoRa ESP32 V2 boards according to IEC 61000-4-3 standards. The tests, conducted in an anechoic chamber at frequencies from 80 MHz to 6 GHz with a field intensity of 10 V/m, revealed sensitivity to EMI at specific frequencies (305 MHz and 730 MHz), leading to packet loss and communication failures. These findings highlight the need for enhanced filtering, shielding, and protocol adjustments to improve the robustness of industrial LoRa-based communications.
Solid Waste Management as an Instrument of Sustainability in Protestant Denominations
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) SILVA, Marcelo Guedes da; ANDRADE, João Bosco Ladislau de; SILVA, Simone da.; LEITE, Jandecy Cabral
This study deals with solid waste management in Protestant Christian religious institutions in the city of Manaus, aiming to evaluate how these institutions manage solid waste and whether they carry out any type of waste management. The applied methodology was descriptive, through observation, registration, analysis, and correlation of the studied facts. Eighteen churches were visited, distributed across all areas of the city, and forms and checklists based on the National Policy on Solid Waste (PNRS) were used. The results showed that there is a great possibility for these Christian communities to serve as environmental schools, promoting societal awareness.
Application of the NARX Model for Forecasting Wind Speed for Wind Energy Generation
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) PARENTE, Ricardo Silva ALENCAR, David Barbosa de SIQUEIRA JUNIOR, Paulo Oliveira SILVA, Ítalo Rodrigo Soares LEITE, Jandecy Cabral; LEITE, Jandecy Cabral
The wind energy matrix has been gradually increasing in recent years and its importance for the renewable energy industry is increasingly linked to environmental benefits. This study applies the NARX model to forecast wind speed in the short term and, consequently, wind energy generation. The research used data from the SONDA project (System of National Organization of Environmental Data), organized by INPE, specifically from the Brasília anemometric station, covering the period from February 2005 to March 2019. The results indicate that the NARX model achieved better performance for short-term forecasts of 10 minutes up to 10 steps ahead, providing greater reliability in wind energy delivery for the energy sector.
Analysis of the Greenhouse Gas Emissions Inventory in a Photographic Paper Finishing Industry in Manaus City
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) MAGALHÃES, Edfran da Cruz SILVA, Simone da; LEITE, Jandecy Cabral
In the Manaus Free Zone, the photographic paper processing industry is poorly representative and classified as a Chemical Industry. This sector has environmental aspects throughout its production processes, including the processing of already emulsified photographic papers, transforming them into necessary sizes and formats for printing. This study investigated greenhouse gas (GHG) emissions in scopes 1 and 2 using the Brazilian GHG Protocol Program (PBGHGP) methodology. The analysis revealed that the main source of GHG emissions originates from the use of R410A refrigerant in the cooling system. The research highlights that proper management of these gases is feasible, as the industry has an environmental management system in place for this control.
Os Impactos Econômicos e Sociais da Repavimentação da BR-319 e Seus Respectivos Desdobramentos Ambientais
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) SOUZA, Luiz Henrique Castelo de SILVA, Simone da; LEITE, Jandecy Cabral
BR-319 is a highway of great importance for the state of Amazonas and other northern regions, directly influencing social, economic, and environmental aspects. The repaving of this road can bring significant benefits, such as job creation and facilitating regional production flow, reducing freight and passenger transport costs. However, the environmental impacts of reconstruction are concerning, including deforestation, natural habitat degradation, chemical pollution, human encroachment, and increased violence. This study analyzes these impacts and suggests mitigation measures to balance economic development and environmental conservation.
A contribuição do cadastro ambiental rural para agricultores familiares no estado do Amazonas, Brasil
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) PAIVA, Ana Paula Cardoso Queiroz de LIMA, Alexandra Amaro de SILVA, Daniel Nascimento e; LEITE, Jandecy Cabral
Environmental issues remain a growing agenda worldwide, with a significant focus on the Amazon. However, the human contingent inhabiting this region, particularly family farmers, is often overlooked. The Rural Environmental Registry (CAR) was created as a tool to promote sustainable public policies and enable environmental and land regularization for these communities. This literature review study investigates CAR's contribution to family farmers in the state of Amazonas from a legal and environmental perspective. The results indicate that understanding the legal aspects and registration process of CAR is essential for compliance. The simplified registration process for family farmers facilitates legal compliance, promoting environmental and land tenure regularization and reducing territorial conflicts. The study concludes that implementing the Brazilian Forest Code, with technical support, is crucial for the sustainability of family farming in the Amazon.
Artificial Neural Networks for Predicting the Generation of Acetaldehyde in PET Resin in the Process of Injection of Plastic Packages
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021) NASCIMENTO, Mauro Reis ALENCAR, David Barbosa de NASCIMENTO, Manoel Henrique Reis MONTEIRO, Carlos Alberto; LEITE, Jandecy Cabral
The industrial production of preforms for PET bottles requires strict control of the PET resin drying temperature to minimize the generation of acetaldehyde (ACH), a compound that can alter the taste of beverages. This study proposes the use of Artificial Neural Networks (ANN) of the Backpropagation type (Cascadeforwardnet) to support decision-making in controlling the ideal drying temperature. The methodology included data collection from the preform injection process and the application of Computational Intelligence techniques to predict ACH levels. The results demonstrate that ANN can optimize the management of production parameters, reducing waste and improving the quality of the final product.