Navegando por Autor "SANTOS, Eliton Smith dos"

Agora exibindo 1 - 5 de 5

Algoritmo para otimizar o processo de inspeção de qualidade
(Instituto Nacional da Propriedade Industrial (INPI), 2024-07-22) SOUSA, Marcio Rizonildo Aquino de; SANTOS, Eliton Smith dos; CAMPOS, Paola Souto; NASCIMENTO, Manoel Henrique Reis; ALENCAR, David Barbosa de
Document for the registration of computer software by the National Institute of Industrial Property (INPI), validating the software "Algorithm to optimize the quality inspection process", developed in Python, valid for 50 years.
Avaliação de imunidade eletromagnética radiada do protocolo IOT LORA
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) RIBEIRO, Jhonatan; SANTOS, Eliton Smith dos
Industrial automation, historically based on wired technologies, has evolved toward wireless solutions, driven by the increasing interconnection of devices and the need to overcome logistical and range limitations. In Industry 4.0, wireless communication plays a central role by integrating sensors, actuators, and control systems into an intelligent production environment. This integration enables real-time data collection and analysis, facilitating automation, optimization, and process flexibility. Despite the benefits, adopting wireless technologies faces significant challenges, particularly electromagnetic interference (EMI), which can compromise the operation of devices and systems. This study presented an analysis of the electromagnetic immunity of the LoRa protocol, using the Heltec V2 board, which incorporates the SX1278 chip, to evaluate its robustness in environments subject to electromagnetic interference. The tests, conducted according to the IEC 61000-4-3 standard, identified critical failure frequencies such as 232.4 MHz, 412 MHz, and 615.2 MHz under different parameter configurations. In these conditions, partial or total communication loss was observed, depending on the intensity of the irradiated field, demonstrating that different configurations can significantly impact the system's immunity. Solutions such as using robust protocols, including LoRaWAN and NB-IoT, spectral spreading techniques, electromagnetic shielding, and filters can mitigate the effects of EMI. Furthermore, future strategies include developing adaptive algorithms to dynamically adjust communication parameters and signal failures, enhancing the resilience and reliability of the LoRa protocol in complex industrial environments. The results of this research contribute to improving wireless communications in Industry 4.0, highlighting LoRa as an essential technology for robust and efficient connectivity.
Implementação de um sistema de visão com deep learning para otimizar o processo de inspeção de emendas das bobinas na fabricação do cinturão de segurança
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) SOUZA, Kerlisson Silva de; SANTOS, Eliton Smith dos
Product quality is one of the primary criteria considered by customers when choosing an item. Additionally, it is an essential factor for companies to stand out in a highly competitive market. In the Manaus Industrial Hub (PIM), in a machine used for producing safety belts, defect detection is a crucial stage in the production process. To enhance this task, Artificial Intelligence (AI) was implemented, standing out for its high efficiency in analyzing and processing data in industrial environments. The data was captured in image format by a camera, and using Deep Learning (DL) techniques, an intelligent algorithm capable of detecting faults was developed. Due to its autonomous learning capability and ability to identify and characterize defects, this algorithm represents the future of automated inspection. It has already achieved significant success in applications such as object identification and classification, facial recognition, and fault diagnostics. Given this context, the aim of this study is to propose an ideal solution to minimize failures in the production process of safety belts. The proposal seeks to automate the currently manual step using the concept of computer vision with AI, ensuring greater efficiency and reliability in the production process. The research, development, and application of AI with the algorithm in the case study were conducted in the R&D laboratory of the company located in the Manaus Industrial Hub (PIM). The project utilized product inputs, a camera equipped with a lens for capturing images, and a computer for data storage and algorithm development. The application of AI in this environment uses computer vision systems to process image data. For this, a program was developed in Python with the PySimpleGUI library. The trained model was evaluated based on loss and accuracy metrics on the test set, achieving values of 0 and 100%, respectively. During testing, new belts were used, reaching 100% accuracy in the results. The proposed model showed excellent results. With data processed by AI using Deep Learning (DL) techniques, real-time inspection of the belts was achieved. Additionally, the network achieved perfect accuracy in all tests conducted on the belts, demonstrating the effectiveness of the solution.
SIMULAÇÃO COMPUTACIONAL NO AUXÍLIO À TOMADA DE DECISÃO NOS PROCESSOS INDUSTRIAIS: UTILIZANDO A FERRAMENTA TECNOMATIX PLANT SIMULATION 9.0
(Universidade Federal do Pará, 2011) SANTOS, Eliton Smith dos; QUARESMA, João Nazareno Nonato
Currently, there are numerous automated production processes that are becoming increasingly complex due to the demands of the modern world. These processes require increasingly powerful engineering tools for efficient modeling and analysis. In this context, the computational tool Tecnomatix Plant Simulation 9.0 emerges as a means of optimizing industrial production. This study presents the application of this tool in modeling and simulating a production line, highlighting its relevance for production management by reducing costs and maximizing profits. The approach is demonstrated through a case study in the electronics industry, analyzing process efficiency and proposing improvements for time and resource optimization.
Simulação Computacional no Auxílio à Tomada de Decisão nos Processos Industriais: Utilizando a Ferramenta Tecnomatix Plant Simulation 9.0
(Universidade Federal do Pará, 2011) SANTOS, Eliton Smith dos; QUARESMA, João Nazareno Nonato
The research presents the use of computer simulation as a tool to aid decision-making in industrial processes, using the Tecnomatix Plant Simulation 9.0 software. The study was applied in a production line of 21" TV sets at the Manaus Industrial Hub, aiming to evaluate the line's performance and propose improvements. The simulation allowed the identification of bottlenecks, the balancing of the production line, and the optimization of resource usage, resulting in a 6.6% increase in daily production. The tool proved effective for preventive and predictive analysis, enabling virtual experiments without interfering with real production.