https://repositorio.ufpb.br/jspui/handle/123456789/2404 2026-06-14T06:01:02Z https://repositorio.ufpb.br/jspui/handle/123456789/38170 Título: Aplicação do Ciclo PDCA para Redução do Indicador de Perdas em uma Fábrica de Têmpera de Vidro em Mossoró-RN Autor(es): Diniz, Diego Henrique da Silva Orientador: Silva, Liane Márcia Freitas e Abstract: The continuous pursuit of industrial process optimization is directly linked to the need to reduce waste and achieve better operational and financial results. In the glass processing sector, efficiency is rigorously measured by the ability to minimize raw material loss during transformation stages. In this context, the problem addressed in this research concerns the high operational loss indicator at a glass tempering factory located in the municipality of MossoróRN, Brazil. Based on a historical analysis of the first five months of 2025, the organization presented an average loss rate of 5.63% relative to total production, falling short of the strategic target of 3% and operating above acceptable industry limits. Therefore, a continuous improvement project grounded in the PDCA Cycle methodology (Plan-Do-Check-Act) was implemented to mitigate this indicator. The investigation of the production process relied on quality tools such as Stratification and the Ishikawa Diagram, which revealed that the root cause of waste was concentrated in the Grinding and Furnace sectors, driven by the absence of standardization and control routines. Corrective and preventive actions were developed through structured action plans, focusing on the implementation of daily inspection checklists, operational training, and the formalization of preventive maintenance. The application took place in two intervention cycles. The first cycle reduced the indicator from 5.63% to 3.42%, representing a 39.25% reduction. With the correction of deviations and the strengthening of managerial monitoring, the second cycle enabled the company to reach a breakage rate of 2.20% in January 2026, representing a total reduction of 60.92% from the beginning of the project to its conclusion, surpassing the established target and proving the method's effectiveness in stabilizing processes and perpetuating good practices on the shop floor. Editor: Universidade Federal da Paraíba Tipo: TCC 2026-04-07T00:00:00Z https://repositorio.ufpb.br/jspui/handle/123456789/38165 Título: Simulação Computacional para Avaliação de Layouts em Processo de Montagem de Livro Capa Dura com Espiral Autor(es): Medeiros, Bruno Lucena de Orientador: Costa, Luciano Carlos Azevedo da Abstract: This undergraduate thesis applied computer simulation to evaluate different layout configurations in a hardcover book assembly process with spiral binding. The study adopted an applied, quantitative, and experimental approach, developed in a printing industry located in João Pessoa, Brazil. Initially, the process was mapped and operational times were collected in the field. The data were statistically analyzed using Python, adjusting probability distributions compatible with the FlexSim simulation software, where the models were built and validated. Two main scenarios were analyzed: Scenario A, which expanded weighing capacity, achieved a 33.6% increase in productivity, while Scenario B, with physical constraints maintained, showed satisfactory performance with a 21.9% increase with fewer operators working. The results demonstrate that simulation is an effective tool for layout improvement and decision support, allowing significant efficiency gains without disrupting real operations. The research contributes to the advancement of knowledge in production engineering and simulation applied to the printing industry, providing a replicable, data-driven methodological framework. Editor: Universidade Federal da Paraíba Tipo: TCC 2026-04-01T00:00:00Z https://repositorio.ufpb.br/jspui/handle/123456789/36175 Título: avaliação e seleção de fundos de investimentos multimercado no Brasil utilizando Análise Envoltória de Dados Autor(es): Andrade, Késsia Gomes Orientador: Rotella Junior, Paulo Abstract: This study proposes the application of Data Envelopment Analysis (DEA) for evaluation and selection of investment funds classified as Multimarket in Brazil as an alternative to traditional performance evaluation methods. The main objective was to identify and select the most efficient funds considering risk, return, cost, and performance consistency criteria. The model used was DEA-BCC output-oriented with computational implementation via Python. The input variables were return volatility over two and five years and the management fee, while the output variables were average annual returns over two and five years and the percentage of months with positive returns over five years. 602 funds were analyzed after a filtering process using Economatica, and the results demonstrated that only 34 funds (5.6% of the sample) reached the efficiency frontier. When compared to the sample, funds considered efficient showed superior average annual returns, greater consistency, lower costs, and lower volatility. The study concludes that DEA is a valuable tool for analysis and selection of Multimarket funds in Brazil and that efficiency is achieved through simultaneous optimization across multiple performance dimensions Editor: Universidade Federal da Paraíba Tipo: TCC 2025-10-06T00:00:00Z https://repositorio.ufpb.br/jspui/handle/123456789/36172 Título: Análise de som para detectar desbalanceamento em um sistema de hélice usando redes neurais convolucionais / Alexandre Sampaio de Figueiredo Autor(es): Figueiredo, Alexandre Sampaio de Orientador: Rodrigues, Marcelo Cavalcanti Abstract: Early fault diagnosis is traditionally performed using vibration analysis, acoustics, and visual inspection techniques; however, these methods have limitations when applied on a large scale or in environments with high noise levels. In this scenario, advances in artificial intelligence, particularly Convolutional Neural Networks CNNs, have enabled new approaches for the automatic detection of anomalies in signals of audio and images. This work presents the application of CNNs to the processing of audio to identify faults in rotating machinery. The experiment consisted of collecting data under two conditions: normal state and with imbalance in one of the propeller blades. The audio signals were processed and transformed into spectrographic representations, allowing them to be used in CNNs for automatic classification. The applied methodology aims to contribute to the advancement of predictive maintenance in machines by offering an artificial intelligence-based approach for diagnosing mechanical faults. Results indicate high model accuracy (100% accuracy, 100% f1- score, 100% precision, 100% recall), demonstrating the viability of the proposal. Editor: Universidade Federal da Paraíba Tipo: TCC 2025-09-24T00:00:00Z