Estudo de diferentes abordagens de gestão de stock usando a simulação
Date
2025
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
IPCB. EST
Abstract
A gestão eficiente de existências (stock) constitui um dos pilares fundamentais para a competitividade e sustentabilidade das organizações, em especial em ambientes caracterizados por elevada variabilidade da procura e complexidade na cadeia de abastecimento. Nesse contexto, diferentes metodologias de planeamento e controlo da produção, envolvendo a reposição de materiais têm sido estudadas e aplicadas, destacando-se entre elas o Reorder Point (ROP) e o Demand Driven Material Requirements Planning (DDMRP). O ROP é talvez a abordagem tradicional de reposição de stock mais conhecida, sendo o DDMRP a abordagem mais moderna. O método tradicional ROP define pontos fixos de reabastecimento para cada um dos produtos em stock, que quando atingidos fazem disparar uma ordem de reposição. Estes são determinados com base no tempo de reposição e no consumo durante esse período,
considerando um stock de segurança para lidar com variações nestes dois. O DDMRP surge como uma abordagem mais recente, concebida para lidar com a volatilidade e incertezas presentes em cadeias de abastecimento modernas, geralmente referido como
proposto para ambiente VUCA (Volatility, Uncertainty, Complexity, Ambiguity). Esta abordagem utiliza conceitos como buffers (stocks) dinâmicos, i.e., ajustáveis ao longo do tempo, net flow e zonamento de stocks, procurando oferecer maior flexibilidade e responsividade às variações, particularmente da procura. O presente estudo tem como objetivo comparar o desempenho destas duas
abordagens, i.e., ROP e DDMRP, num ambiente de produção capacitada, por meio da simulação computacional, permitindo avaliar a eficácia de cada abordagem em diferentes condições operacionais. A simulação é utilizada como ferramenta de análise por possibilitar
a reprodução de cenários complexos, realistas, e com estocacidade, sem a necessidade de intervenção direta no ambiente produtivo real, como eventuais perturbações ao seu funcionamento. Dessa forma, torna-se possível observar como cada abordagem se comporta sob condições operacionais distintas, variando o posicionamento dos buffers no sistema de produção, e variando parâmetros operacionais do ROP e do DDMRP. A análise busca evidenciar os impactos de cada abordagem em indicadores-chave de desempenho, tais como nível de serviço, tempo de percurso, quantidade em stock nos buffers e em curso (work-in-process: WIP). Assim, este estudo pretende fornecer uma base sólida para a tomada de decisão em gestão de stock. Em síntese, a análise proposta procura orientar os gestores industriais na escolha da abordagem mais adequada. Os resultados obtidos com o sistema de reposição
DDMRP revelam-se praticamente idênticos aos obtidos através do sistema ROP.
Abstract: Efficient inventory management is one of the fundamental pillars for the competitiveness and sustainability of organizations, especially in environments characterized by high demand variability and supply chain complexity. In this context, different production planning and control methodologies involving material replenishment have been studied and applied, notably Reorder Point (ROP) and Demand-Driven Material Requirements Planning (DDMRP). ROP is perhaps the best-known traditional inventory replenishment approach, with DDMRP being the more modern approach. ROP defines fixed reorder points for each product in stock, which, when reached, trigger a replenishment order. These are determined based on replenishment lead time and consumption during that period, considering a safety stock to handle variations in both. DDMRP emerges as a more recent approach, designed to address the volatility and uncertainties present in modern supply chains, generally referred to as a proposal for a VUCA (Volatility, Uncertainty, Complexity, Ambiguity) environment. This approach utilizes concepts such as dynamic buffers (stocks), i.e., adjustable overtime, net flow, and inventory zoning, seeking to offer greater flexibility and responsiveness to variations, particularly in demand.This study aims to compare the performance of these two approaches, i.e., ROP and DDMRP, in a capable production environment through computer simulation, allowing us to evaluate the effectiveness of each approach under different operating conditions. Simulation is used as an analysis tool because it enables the reproduction of complex, realistic, and stochastic scenarios without the need for direct intervention in the real production environment, such as potential disruptions to its operation. This makes it possible to observe how each approach behaves under different operating conditions, varying parameters such as the positioning of buffers in the production system and the operational parameters of ROP and DDMRP. The analysis seeks to highlight the impacts of each approach on key performance indicators, such as service level, transit time, average buffer and work-in-process (WIP) inventory levels, and production resource utilization. Thus, this study aims to provide a solid basis for inventory management decision-making. In short, the proposed analysis aims to guide industrial managers in choosing the most appropriate approach. The results obtained with the DDMRP replenishment system are virtually identical to those obtained with the ROP system.
Abstract: Efficient inventory management is one of the fundamental pillars for the competitiveness and sustainability of organizations, especially in environments characterized by high demand variability and supply chain complexity. In this context, different production planning and control methodologies involving material replenishment have been studied and applied, notably Reorder Point (ROP) and Demand-Driven Material Requirements Planning (DDMRP). ROP is perhaps the best-known traditional inventory replenishment approach, with DDMRP being the more modern approach. ROP defines fixed reorder points for each product in stock, which, when reached, trigger a replenishment order. These are determined based on replenishment lead time and consumption during that period, considering a safety stock to handle variations in both. DDMRP emerges as a more recent approach, designed to address the volatility and uncertainties present in modern supply chains, generally referred to as a proposal for a VUCA (Volatility, Uncertainty, Complexity, Ambiguity) environment. This approach utilizes concepts such as dynamic buffers (stocks), i.e., adjustable overtime, net flow, and inventory zoning, seeking to offer greater flexibility and responsiveness to variations, particularly in demand.This study aims to compare the performance of these two approaches, i.e., ROP and DDMRP, in a capable production environment through computer simulation, allowing us to evaluate the effectiveness of each approach under different operating conditions. Simulation is used as an analysis tool because it enables the reproduction of complex, realistic, and stochastic scenarios without the need for direct intervention in the real production environment, such as potential disruptions to its operation. This makes it possible to observe how each approach behaves under different operating conditions, varying parameters such as the positioning of buffers in the production system and the operational parameters of ROP and DDMRP. The analysis seeks to highlight the impacts of each approach on key performance indicators, such as service level, transit time, average buffer and work-in-process (WIP) inventory levels, and production resource utilization. Thus, this study aims to provide a solid basis for inventory management decision-making. In short, the proposed analysis aims to guide industrial managers in choosing the most appropriate approach. The results obtained with the DDMRP replenishment system are virtually identical to those obtained with the ROP system.
Description
Keywords
DDMRP, ROP, Simulação, Gestão de Stock, Simulation, Inventory Managemen
Citation
DJABI, Suleimane (2025) - Estudo de diferentes abordagens de gestão de stock usando a simulação. Castelo Branco : IPCB. EST. 54 p. Relatório do Trabalho de Fim de Curso de Engenharia e Gestão Industrial.