Loading...
Publication
Melhoria dos processos de armazenagem através de automação e simulação computacional
| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 5.86 MB | Adobe PDF |
Authors
Advisor(s)
Abstract(s)
A presente dissertação centra-se na análise e melhoria dos processos logísticos de
armazenagem de uma empresa do setor de transportes, e propõe a aplicação da metodologia
PDCA em articulação com simulação computacional como ferramentas de apoio à decisão.
O estudo nasce da necessidade crescente de responder aos desafios de eficiência
operacional e redução de erros associados à gestão tradicional de armazéns, ainda
fortemente dependente da intervenção humana.
Numa primeira fase, foi realizada uma revisão bibliográfica detalhada sobre armazenagem,
metodologias de melhoria contínua, inovação tecnológica e ferramentas de simulação. Esta
fundamentação permitiu enquadrar a investigação na realidade atual das cadeias de
abastecimento, onde a digitalização e a automação se apresentam como elementos-chave
para a competitividade. Em seguida, foi aplicado um caso de estudo à empresa Europackers,
onde se procedeu ao mapeamento dos processos logísticos existentes e se identificou pontos
críticos que comprometiam a eficiência global do sistema.
Com base na metodologia PDCA, foram definidas ações de melhoria e desenvolvidos
modelos de simulação para as soluções propostas no software JaamSim, versão 2024.9.00,
testando-se três cenários distintos: processo manual (estado atual), processo
semiautomático e processo totalmente automatizado. As simulações foram realizadas em
ambiente tridimensional (3D), o que permitiu uma representação visual mais realista dos
processos, e a análise dos resultados foi complementada com códigos desenvolvidos em
Python, que possibilitaram o tratamento estatístico dos dados e a geração automatizada de
gráficos comparativos.
Os resultados evidenciam ganhos significativos de eficiência nos cenários com maior grau de
automatização, com destaque para a redução dos tempos de processamento, redução de
trabalhadores (requalificação para outras tarefas) e menor dependência do esforço físico dos
colaboradores necessários. Estes ganhos validam a aplicação conjunta da metodologia
PDCA e da simulação computacional como estratégia eficaz para a modernização e melhoria
dos processos de armazenagem.
Este trabalho contribui, assim, para a consolidação do conhecimento na área da gestão
logística e cadeia de abastecimento e oferece uma abordagem prática e replicável para
organizações que procuram alinhar-se com as exigências atuais do mercado, onde a melhoria
contínua sustentada por dados e tecnologia é fulcral para a sobrevivência e posicionamento
das mesmas.
This dissertation focuses on the analysis and optimization of warehousing logistics processes within a transport sector company, proposing the integrated use of the PDCA methodology and computer simulation as decision-support tools. The study responds to the increasing need for greater operational efficiency and error reduction in warehouse management, which is still largely dependent on manual operations. The research begins with a comprehensive literature review on warehousing systems, continuous improvement methodologies, technological innovation, and simulation tools. This review frames the study within the evolving context of supply chains, where digitalization and automation are essential for competitiveness. A study was carried out at the company Europackers, involving the mapping of the current logistics processes and the identification of critical inefficiencies affecting the overall system performance. Following the PDCA methodology, specific improvement actions were defined and simulation models were developed in JaamSim (version 2024.9.00). Three distinct scenarios were tested: the current manual process, a semi-automated process, and a fully automated process. These simulations were conducted in a three-dimensional (3D) environment for enhanced realism, and the analysis was supported by Python scripts for statistical processing and automated generation of comparative performance graphs. The simulations enabled a robust comparison of the scenarios, assessing processing times, workforce utilization, physical effort, responsiveness, and internal organization. The results clearly highlight efficiency improvements in the more automated scenarios, including shorter processing times, reduced physical demands, and the potential for workforce reallocation to higher-value tasks. These outcomes validate the effectiveness of combining PDCA with computer simulation as a strategic approach for modernizing warehousing operations. This work contributes to the field of logistics and supply chain management by presenting a data-driven, technology-supported methodology that is both practical and replicable, supporting organizations in meeting current market demands through continuous improvement and operational excellence.
This dissertation focuses on the analysis and optimization of warehousing logistics processes within a transport sector company, proposing the integrated use of the PDCA methodology and computer simulation as decision-support tools. The study responds to the increasing need for greater operational efficiency and error reduction in warehouse management, which is still largely dependent on manual operations. The research begins with a comprehensive literature review on warehousing systems, continuous improvement methodologies, technological innovation, and simulation tools. This review frames the study within the evolving context of supply chains, where digitalization and automation are essential for competitiveness. A study was carried out at the company Europackers, involving the mapping of the current logistics processes and the identification of critical inefficiencies affecting the overall system performance. Following the PDCA methodology, specific improvement actions were defined and simulation models were developed in JaamSim (version 2024.9.00). Three distinct scenarios were tested: the current manual process, a semi-automated process, and a fully automated process. These simulations were conducted in a three-dimensional (3D) environment for enhanced realism, and the analysis was supported by Python scripts for statistical processing and automated generation of comparative performance graphs. The simulations enabled a robust comparison of the scenarios, assessing processing times, workforce utilization, physical effort, responsiveness, and internal organization. The results clearly highlight efficiency improvements in the more automated scenarios, including shorter processing times, reduced physical demands, and the potential for workforce reallocation to higher-value tasks. These outcomes validate the effectiveness of combining PDCA with computer simulation as a strategic approach for modernizing warehousing operations. This work contributes to the field of logistics and supply chain management by presenting a data-driven, technology-supported methodology that is both practical and replicable, supporting organizations in meeting current market demands through continuous improvement and operational excellence.
Description
Keywords
Warehousing Computer Simulation PDCA Automation Operational Efficiency Armazenagem Simulação computacional Automatização Eficiência operacional