https://repositorio.ufba.br/handle/ufba/561 Mestrado acadêmico Sat, 02 May 2026 12:39:29 GMT 2026-05-02T12:39:29Z https://repositorio.ufba.br/handle/ri/44096 Título: Utilização da simulação no contexto da Learning Factory: aplicação inserida na fase 1 do gêmeo digital Autor(es): Araujo, Andressa Clara Barbosa de Primeiro Orientador: Pimentel, Cristiane Agra Abstract: Industry 4.0 has driven profound transformations in production models, standing out for the use of enabling technologies such as simulation and digital twins. In this context, the objective of this dissertation was to develop a computational model representing the manufacturing flow of a product in a Learning Factory, using simulation as Phase I of the Digital Twin. The study is justified by the growing demand for industrial digitalization and by the lack of practical cases of implementation of technologies such as Digital Twins, especially in low-automation environments. Thus, the research proposes the use of simulation as an initial stage for the development of digital twins in Learning Factories, contributing to local innovation and to applied studies in the field. Methodologically, the study adopted an applied and explanatory approach, with a quantitative basis and technical procedures involving case study and action research. Discrete-event simulation was employed using the FlexSim® software, version 24.2.1. The model development followed DMAIC methodology (Define, Measure, Analyze, Improve, and Control), integrating Industry 4.0 concepts and emerging digital technologies. The simulated environment was a 60 m² Learning Factory with 19 workstations and capacity for 17 operators, arranged in a serial production layout. The results obtained from the simulation made it possible to validate the proposed Learning Factory layout and to perform productivity analyses based on simulated data, providing support for optimizing production flows without interventions in the real environment. The computational model proved viable for testing different improvement scenarios, anticipating bottlenecks, and facilitating the planning of physical and operational changes. Computational simulation is an efficient tool for the development of digital models of production environments, playing a strategic role in the first phase of Digital Twin implementation. The study highlights the importance of Learning Factories as innovation laboratories and demonstrates the applicability of simulation for process optimization and support for industrial digitalization, contributing to the advancement of Industry 4.0 in the national context. Editora / Evento / Instituição: Universidade Federal da Bahia Tipo: Dissertação Wed, 28 Jan 2026 00:00:00 GMT https://repositorio.ufba.br/handle/ri/44096 2026-01-28T00:00:00Z https://repositorio.ufba.br/handle/ri/44031 Título: Modelagem de séries temporais para previsão de vazões em rios com monitoramento hidrológico Autor(es): Silva, Ricardo Aragão e Primeiro Orientador: Sant'Anna, Ângelo Márcio Oliveira Abstract: Water resources play a vital role in a country's development. Streamflow is the primary variable monitored at gauging stations, however measuring this variable involves significant risks and high operational costs. The Brazilian National Hydrometeorological Network (RHN), operated by the Geological Survey of Brazil (SGB) in partnership with the National Water Agency (ANA), provides essential historical datasets for streamflow forecasting. This study aims to develop time series models to forecast monthly river discharges, using as case studies the gauging stations of Santa Maria da Vitória (1977–2022) and Batalha (2015–2023), both located in Bahia. The research employs ARIMA models, implemented in the R Core Team (2025), to evaluate the accuracy and applicability of forecasts at various temporal horizons. The results demonstrate that the ARIMA (3,0,3)(3,1,1) model achieved a satisfactory fit, with robust error metrics (MAPE, RMSE, and MAE). Statistical tests confirmed stationarity. The forecasts closely followed the historical series’ behavior, providing consistent estimates up to 12 months ahead. It is concluded that time series modeling is a promising tool to complement the traditional rating curves, enabling greater simplicity and reliability in streamflow predictions. This approach can further support water resources management and hydrological alert systems in critical events such as droughts and floods. Additionally, it contributes to the design of hydraulic structures and water allocation processes, strengthening the use of quantitative data and statistical techniques as decision-support tools in hydrology. Editora / Evento / Instituição: UNIVERSIDADE FEDERAL DA BAHIA Tipo: Dissertação Thu, 01 Dec 0012 00:00:00 GMT https://repositorio.ufba.br/handle/ri/44031 0012-12-01T00:00:00Z https://repositorio.ufba.br/handle/ri/43846 Título: Lean Manufacturing e Tecnologias da Indústria 4.0 em Pequenas e Médias Empresas para Eficiência Operacional Autor(es): Borges, Tiago de Sena Primeiro Orientador: Sant’Anna, Ângelo Márcio Oliveira Abstract: Lean Manufacturing combined with Industry 4.0 (I4.0) technologies proposes a new perspective for industrial advancement. However, several aspects still require investigation, especially in the context of small and medium-sized enterprises (SMEs). The objective of this research is to present guidelines that support the implementation of Lean 4.0 in SMEs in the pursuit of operational efficiency. This work conducted a systematic literature review and collected empirical evidence through field research, focused on the integration between Lean Manufacturing and I4.0 technologies as a means of achieving greater operational efficiency in SMEs. The results obtained from the systematic literature review were analyzed from articles in the Web of Science and Scopus databases. The PRISMA methodology was adopted to select publications based on predefined criteria. The R® software was used to analyze the growth of publications by country, application areas, journals, among others, and the Vosviewer® software was used to map the main keywords and their connections. The results allowed for the identification of the tools most frequently associated with Industry 4.0 technologies in SMEs and the resulting benefits of this integration. Field research allowed for the evaluation of the results of digitizing Lean Manufacturing, Just-in-Time, Kanban, and 5S tools in Software as a Service (SaaS). Reductions in waste due to overproduction, unnecessary deliveries, decreased setup time, and a more organized work environment were observed. Furthermore, it was possible to assess the main guidelines in the Lean 4.0 implementation process in the company studied. Editora / Evento / Instituição: Universidade Federal da Bahia Tipo: Dissertação Tue, 02 Dec 2025 00:00:00 GMT https://repositorio.ufba.br/handle/ri/43846 2025-12-02T00:00:00Z https://repositorio.ufba.br/handle/ri/43820 Título: Modelagem e Simulação do Processo de Produção de Querosene de Aviação Sustentável Autor(es): Borges, Raiane Pereira de Sá Primeiro Orientador: Torres, Ednildo Andrade Abstract: Over the last decade, the aviation industry has experienced significant expansion in global air travel, driving socioeconomic growth and worldwide connectivity; however, this progress has also increased the dispersion of greenhouse gas (GHG) emissions, intensifying environmental impacts on a planetary scale. As a result, Sustainable Aviation Fuel (SAF), an alternative aviation kerosene, has emerged as a sustainable energy solution for the aeronautical industry, being produced from non-conventional sources and having its adoption conditioned by environmental, social, technological, and economic indicators that determine its feasibility and competitiveness. Research in this field, particularly in Brazil, has grown exponentially, positioning the country as a potential hub for SAF production. This biojet fuel represents a viable solution for reducing carbon emissions, as it can be produced from a wide range of renewable sources, including vegetable oils, agro-industrial residues, and lignocellulosic biomass. Such research frequently relies on modeling and simulation software to analyze and optimize production processes, aiming to reduce losses, improve efficiency, and increase profitability. The production of this alternative kerosene follows international standards such as ASTM D1655 and ASTM D7566, as well as national regulations, including ANP Resolution No. 856/2021 in Brazil, which establishes technical requirements for quality, safety, and commercialization. The main technological routes include Alcohol-to-Jet (ATJ), Hydroprocessed Esters and Fatty Acids (HEFA), and Fischer–Tropsch (FT), each defined by distinct feedstocks and specific conversion processes. This research proposes the development of a computational modeling and simulation of the SAF production process, focusing on the HEFA pathway, which was selected due to its higher technological maturity and energy efficiency compared to the other evaluated alternatives. The modeling will be based on a comprehensive state-of-the-art review to develop a tool for evaluating and optimizing operational parameters, with the objective of increasing production efficiency. This study constitutes the initial stage of a broader project aimed at optimizing SAF production and reducing losses and uncertainties in future experimental studies within the CATSAF/UFBA project. Editora / Evento / Instituição: Universidade Federal da Bahia Tipo: Dissertação Tue, 18 Nov 2025 00:00:00 GMT https://repositorio.ufba.br/handle/ri/43820 2025-11-18T00:00:00Z