Artigos

URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/5

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Application of ergonomic work analysis in automotive industry processes using computational intelligence for decision making
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2022-02-26) PINTO, Leandro Soares; LEITE, Jandecy Cabral
Ergonomics have proved to be increasingly important for industrial processes around the world. The evolution of machinery and equipment has caused several disorders in occupational health at work. Therefore, it is extremely important to make a comprehensive reading of the workstations and ergonomic analysis tools. The objective of the article is to make an application of the technological resources of fuzzy logic in the results found in the Ergonomic Analysis of Work (AET) in seven jobs in the automotive industry of the Industrial Pole of Manaus (PIM). The methodology applied is based on the application of ergonomic tools using Suzanne Rodgers`method and on the mathematical models characterized by Fuzzy Inference for decision making on various disorders that occur with the health of the employee. The results found in the ergonomic tool ‘’Suzanne Rodgers’’ applied to the movement of upper and lower limbs and other observations in the productive sectors, with the application of Fuzzy Logic, it was shown that the linguistic variables by colors, the legend that shows the classification of ergonomic risks through run. Therefore, they serve to make a comparison and discuss the importance of ergonomic processes for the benefit of the worker in the automotive industry for decision-making.
Compliance application process as a strategic tool in the management of a third sector organization
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021-05-01) MELO, Maria Lidelmar Carvalho de; LEITE, Jandecy Cabral; SILVA, Ítalo Rodrigo Soares; SIQUEIRA junior, Paulo Oliveira
Adapting to integrity models that respect the current legislation has become fundamental in the management of organizations as a strategic form, mainly in entities with public and non-profit purposes, in a non-governmental scope. Therefore, the objective is to implement a model for the application of the compliance program in a Third Sector institution. In this way, the present article can be considered in an exploratory, applied and qualitative way, in two aspects, bibliographic research and case study, the data collection was through a meeting and interview with the company's professionals, reporting the importance of the theme. The results showed the main tools and compliance mechanism, proposing actions that can be used in practice with the purpose of providing a broad view of the functioning of the proposed model, with transparency and ethics, thus increasing the competitiveness of the business.
Computational meta-heuristics based on Machine Learning to optimize fuel consumption of vessels using diesel engines
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2021-05-01) SIQUEIRA JUNIOR, Paulo Oliveira; NASCIMENTO, Manoel Henrique Reis; SILVA, Ítalo Rodrigo Soares; PARENTE, Ricardo Silva; FONSECA JUNIOR, Milton; LEITE, Jandecy Cabral;
With the expansion of means of river transportation, especially in the caseof small and medium-sized vessels that make routes of greater distances, the cost of fuel, if not taken as an analysis criterion for a larger profit margin, is considered to be a primary factor , considering that the value of fuel specifically diesel to power internal combustion machines is high. Therefore, the use of tools that assist in decision making becomes necessary, as is the case of the present research, which aims to contribute with a computational model of prediction and optimization of the best speed to decrease the fuel cost considering the characteristics of the SCANIA 315 machine. propulsion model, of a vessel from the river port of Manaus that carries out river transportation to several municipalities in Amazonas. According to the results of the simulations, the best training algorithm of the Artificial Neural Network (ANN) was the BFGS Quasi-Newton considering the characteristics of the engine for optimization with Genetic Algorithm (AG).
Developing An AMR Prototype With Processing Offloading Using 5G Servers For Industry 4.0
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024-09-01) COSTA, Gledyson Cidade da; RODRÍGUEZ, Carlos Manoel Taboada; LEITE, Jandecy Cabral
This study explores the development of an autonomous mobile robot (AMR) prototype with processing offloading using 5G servers for Industry 4.0. The goal is to improve AMR performance by reducing the computational load on the robot and optimizing energy efficiency. The developed architecture integrates the AMR with the 5G infrastructure, distributing processing between the robot and external servers, enabling real-time response. The results show that this approach improves AMR navigation and efficiency in industrial environments.
Development of a Prototype Gateway for Data Collection and Transmission in Material Handling Systems - Gate Move 4.0
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024-06-09) AMARAL, Carlos Henrique; LEITE, Jandecy Cabral; RIBEIRO, Paulo Francisco da Silva; SILVA, Ítalo Rodrigo Soares; PARENTE, Ricardo Silva; DIRANE, Eduardo Nunes; MENDONÇA, Pedro Henrique Barros
The article discusses the development of a gateway prototype named Gate Move 4.0, designed for data collection and transmission in material handling systems. The goal of the study is to improve operational efficiency and decision-making in industries, especially with the advent of Industry 4.0. The prototype was evaluated under various operating conditions, demonstrating efficiency in data collection, connectivity, and performance in adverse environments. The methodology included requirements analysis and the implementation of sensor technologies and communication protocols. Results showed that Gate Move 4.0 is a viable solution for material handling systems.
Fuzzy Logic-Based Compliance Assessment For Display Testing In Industrial Measurement Systems
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024-10-01) SOUZA, Márcio André de Oliveira; NASCIMENTO, Manoel Henrique Reis; LEITE, Jandecy Cabral; BRITO JUNIOR, Jorge de Almeida; QUEIROZ JUNIOR, Fernando Cardoso de
This study presents the development and implementation of a fuzzy logic-based system aimed at automating the compliance evaluation process for display testing in industrial measurement systems. The fuzzy inference system was programmed in Python, using linguistic variables and fuzzy rules to assess performance parameters like accuracy, response time, and error margins. Results showed that the system classified 93% of devices in accordance with established compliance standards, improving the reliability and efficiency of display testing in industrial environments.