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Advisor(s)
Abstract(s)
Esta dissertação tem como objetivo desenvolver uma metodologia que permita adequar a
capacidade de produção à procura do mercado na fábrica de motores elétricos da WEGeuro.
Para isso, foi criada uma ferramenta capaz de calcular com precisão os tempos de produção dos
componentes críticos, utilizando parâmetros específicos de máquinas CNC (Computer Numeric
Control), e outra ferramenta destinada ao controle de carga de trabalho da empresa.
Inicialmente, foi realizada uma análise detalhada do processo produtivo, identificando os
componentes que mais influenciam o tempo de maquinagem, como as carcaças e caixas de
ligação. A partir dessa análise, foi desenvolvido um software em Excel VBA para calcular os
tempos de operação de acordo com as características dos componentes, proporcionando uma
estimativa mais confiável e precisa dos tempos de produção. Além disso, uma ferramenta em
Power BI foi implementada para visualizar e gerenciar a carga de trabalho em tempo real,
otimizando a alocação de recursos e melhorando a eficiência operacional. A demonstração dos
resultados indicou que as ferramentas desenvolvidas contribuíram significativamente para a
redução de custos e aumento da produtividade, uma vez que permitiram uma melhor gestão
dos recursos e a eliminação de etapas improdutivas no processo de fabricação. A conclusão
reforça que a metodologia proposta conseguiu atingir os objetivos traçados, destacando a
importância da integração entre o cálculo preciso dos tempos de produção e o controlo de
cargas para a melhoria contínua da eficiência industrial. As ferramentas desenvolvidas
mostraram-se eficazes em adaptar a capacidade de produção às variações da demanda,
proporcionando uma base sólida para futuras melhorias no planeamento e controlo da
produção na fábrica.
This dissertation aims to develop a methodology that enables the adjustment of production capacity to market demand at the WEGeuro electric motor factory. To achieve this, a tool was created to accurately calculate the production times of critical components using specific CNC machine parameters, along with another tool designed for workload management within the company. Initially, a detailed analysis of the production process was conducted, identifying the components that most significantly impact machining time, such as casings and junction boxes. Based on this analysis, an Excel VBA software was developed to calculate operation times according to the characteristics of the components, providing a more reliable and precise estimate of production times. Additionally, a tool in Power BI was implemented to visualize and manage the workload in real-time, optimizing resource allocation and improving operational efficiency. The demonstration of results indicated that the developed tools significantly contributed to cost reduction and productivity improvement, as they allowed for better resource management and the elimination of non-productive steps in the manufacturing process. The conclusion reinforces that the proposed methodology successfully achieved the outlined objectives, highlighting the importance of integrating precise production time calculations with workload management for the continuous improvement of industrial efficiency. The developed tools proved effective in adapting production capacity to demand variations, providing a solid foundation for future improvements in production planning and control at the factory.
This dissertation aims to develop a methodology that enables the adjustment of production capacity to market demand at the WEGeuro electric motor factory. To achieve this, a tool was created to accurately calculate the production times of critical components using specific CNC machine parameters, along with another tool designed for workload management within the company. Initially, a detailed analysis of the production process was conducted, identifying the components that most significantly impact machining time, such as casings and junction boxes. Based on this analysis, an Excel VBA software was developed to calculate operation times according to the characteristics of the components, providing a more reliable and precise estimate of production times. Additionally, a tool in Power BI was implemented to visualize and manage the workload in real-time, optimizing resource allocation and improving operational efficiency. The demonstration of results indicated that the developed tools significantly contributed to cost reduction and productivity improvement, as they allowed for better resource management and the elimination of non-productive steps in the manufacturing process. The conclusion reinforces that the proposed methodology successfully achieved the outlined objectives, highlighting the importance of integrating precise production time calculations with workload management for the continuous improvement of industrial efficiency. The developed tools proved effective in adapting production capacity to demand variations, providing a solid foundation for future improvements in production planning and control at the factory.
Description
Keywords
Process diagram Operations plan Methods and time study Workload management Diagrama de processo Plano de operações Estudo de métodos e tempos Controlo de cargas