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Otimização em operações de logística: impacto nas operações de picking numa empresa 3PL
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Num setor marcado por elevados níveis de exigência e complexidade, a eficiência na
preparação de pedidos assume um papel central na competitividade das operações logísticas.
Esta dissertação incide sobre a análise e otimização do processo de picking de um operador logístico
3PL, com enfoque num cliente estratégico da Luís Simões.
Com base numa abordagem estruturada segundo o ciclo PDCA, foi realizado um diagnóstico
detalhado aos clientes e artigos, com o objetivo de compreender a realidade operacional —
correspondendo à fase de Planeamento.
A partir desta análise, foram desenvolvidas três soluções complementares: um algoritmo
de roteamento baseado em boas práticas implementadas pelos operadores; uma aplicação, criada
em PowerApps de apoio à gestão das diferentes localizações e movimentos do armazém—
desenvolvida e aprovada pela equipa de layout; e um modelo digital do processo, desenvolvido em
FlexSim, de modo a testar várias soluções sem o risco operacional associado.
O Modelo Digital atual permite simular o processo de preparação de pedido de guias
simples e extração de indicadores. O algoritmo foi testado no modelo, com dados operacionais, e,
demonstrou reduções de 13% no tempo de execução e de 20% na distância percorrida. A aplicação
é uma ferramenta de apoio à decisão, de centralização e visualização clara de dados operacionais.
As soluções propostas demonstram potencial para reduzir tempos de preparação,
minimizar o desgaste dos operadores e sustentar decisões operacionais baseadas em dados. No
seu conjunto, representam um primeiro passo rumo à digitalização avançada da operação de
picking, integrada com os sistemas da empresa, capaz de testar cenários, antecipar impactos e
apoiar decisões estratégicas num ambiente logístico cada vez mais exigente.
O ciclo PDCA encontra-se atualmente na fase Check, com as soluções em fase de evolução
e testes, de forma a garantir a sua escalabilidade.
In a sector characterized by high levels of complexity and operational demands, efficiency in order picking plays a central role in the competitiveness of logistics operations. This dissertation focuses on the analysis and optimization of the picking process of a 3PL logistics operator, with particular emphasis on a strategic client of Luís Simões. Based on a structured approach following the PDCA cycle, a detailed diagnosis was conducted on clients and items, aiming to understand the operational reality — corresponding to the Planning phase. From this analysis, three complementary solutions were developed: a routing algorithm based on best practices implemented by operators; a decision-support application developed in Power Apps to manage warehouse locations and movements — approved by the company's layout team; and a digital model of the process, built in FlexSim, to test different solutions without the associated operational risk. The current digital model allows the simulation of the picking process for simple orders and the extraction of performance indicators. The routing algorithm was tested in the model using operational data, showing reductions of 13% in execution time and 20% in travel distance. The application serves as a decision-support tool, enabling centralized and clear visualization of operational data. The proposed solutions show strong potential to reduce picking times, minimize operator fatigue, and support data-driven operational decisions. Together, they represent a first step toward the advanced digitalization of the picking process, paving the way for the creation of a Digital Twin integrated with the company's systems — capable of testing scenarios, anticipating impacts, and supporting strategic decisions in an increasingly demanding logistics environment. The PDCA cycle is currently at the Check phase, with the solutions undergoing further development and testing to ensure their scalability.
In a sector characterized by high levels of complexity and operational demands, efficiency in order picking plays a central role in the competitiveness of logistics operations. This dissertation focuses on the analysis and optimization of the picking process of a 3PL logistics operator, with particular emphasis on a strategic client of Luís Simões. Based on a structured approach following the PDCA cycle, a detailed diagnosis was conducted on clients and items, aiming to understand the operational reality — corresponding to the Planning phase. From this analysis, three complementary solutions were developed: a routing algorithm based on best practices implemented by operators; a decision-support application developed in Power Apps to manage warehouse locations and movements — approved by the company's layout team; and a digital model of the process, built in FlexSim, to test different solutions without the associated operational risk. The current digital model allows the simulation of the picking process for simple orders and the extraction of performance indicators. The routing algorithm was tested in the model using operational data, showing reductions of 13% in execution time and 20% in travel distance. The application serves as a decision-support tool, enabling centralized and clear visualization of operational data. The proposed solutions show strong potential to reduce picking times, minimize operator fatigue, and support data-driven operational decisions. Together, they represent a first step toward the advanced digitalization of the picking process, paving the way for the creation of a Digital Twin integrated with the company's systems — capable of testing scenarios, anticipating impacts, and supporting strategic decisions in an increasingly demanding logistics environment. The PDCA cycle is currently at the Check phase, with the solutions undergoing further development and testing to ensure their scalability.
Descrição
Palavras-chave
Otimização de operações logísticas Gestão de armazéns Estratégias de slotting Algoritmos de picking Simulação Logistics operations optimization Warehouse management Slotting strategies Order picking algorithms Simulation