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Abstract(s)
A Indústria 4.0 representa uma revolução na manufatura, integrando tecnologias avançadas como a Internet das Coisas (IoT), modelos de simulação e big data para criar fábricas mais eficientes, flexíveis e interconectadas. No âmbito desta dissertação, desenvolveu-se uma ferramenta de apoio à decisão que utiliza a simulação para modelar e melhorar processos produtivos. Para a construção dos modelos de simulação, foi utilizado o open-source software JaamSim. A análise simultânea dos resultados foi realizada através da integração dos relatórios com o Power BI, uma plataforma de business intelligence que permite a visualização interativa dos dados. A metodologia envolveu a simulação de diversos cenários de produção, variando o número de operadores e estratégias de escalonamento da produção. No sentido de validar a ferramenta,
foram executados e analisados quatro cenários com as necessidades da semana 25 do ano de 2024. Os resultados indicaram que as estratégias com três operadores, especialmente quando a produção foi organizada por famílias, apresentaram uma maior ocupação e eficiência produtiva. Em contraste, os cenários com apenas dois operadores mostraram dificuldades em manter a produtividade desejada e, consequentemente, o cumprimento dos prazos de entrega. A ferramenta destaca a importância de uma alocação flexível dos recursos humanos para responder à variabilidade da procura. Desta forma, demonstrou-se a eficácia das tecnologias da Indústria 4.0 na melhoria da gestão da produção e abriu novas perspetivas para a implementação de soluções mais avançadas e integradas, contribuindo significativamente para a competitividade e eficiência da linha produtiva.
The Industry 4.0 represents a revolution in manufacturing, integrating advanced technologies such as the Internet of Things (IoT), simulation models and big data to create more efficient, flexible and interconnected factories. As the subject of this dissertation, a decision support tool has been developed that uses simulation to model and improve production processes. The open-source software JaamSim was used to build the simulation models, and the results were analyzed simultaneously by integrating the reports with Power BI, a business intelligence platform that allows interactive data visualization. The methodology involved simulating various production scenarios, varying the number of operators and production scheduling strategies. To analyze the usability of the tool, the scenarios with the demands of week 25 of the year 2024 were executed and analyzed. The results indicated that the scenarios with three operators, especially when production was organized by families, showed higher capacity and production efficiency. In contrast, the scenarios with only two operators showed difficulties in maintaining the required productivity and consequently complying with lead times. The effectiveness of Industry 4.0 technologies in improving production management has thus been demonstrated and new perspectives created for the implementation of more advanced and integrated solutions, contributing significantly to the competitiveness and efficiency of the production line.
The Industry 4.0 represents a revolution in manufacturing, integrating advanced technologies such as the Internet of Things (IoT), simulation models and big data to create more efficient, flexible and interconnected factories. As the subject of this dissertation, a decision support tool has been developed that uses simulation to model and improve production processes. The open-source software JaamSim was used to build the simulation models, and the results were analyzed simultaneously by integrating the reports with Power BI, a business intelligence platform that allows interactive data visualization. The methodology involved simulating various production scenarios, varying the number of operators and production scheduling strategies. To analyze the usability of the tool, the scenarios with the demands of week 25 of the year 2024 were executed and analyzed. The results indicated that the scenarios with three operators, especially when production was organized by families, showed higher capacity and production efficiency. In contrast, the scenarios with only two operators showed difficulties in maintaining the required productivity and consequently complying with lead times. The effectiveness of Industry 4.0 technologies in improving production management has thus been demonstrated and new perspectives created for the implementation of more advanced and integrated solutions, contributing significantly to the competitiveness and efficiency of the production line.
Description
Keywords
Simulation Software Jaam Sim Production Planning Resource Allocation Simulação Planeamento da produção Alocação de recursos