The DDMRP Replenishment Model: An Assessment by Simulation

Demand-Driven Material Requirements Planning (DDMRP) has been proposed as a solution for managing uncertainty and variability in supply chains by combining decoupling, buffer management and demand-driven planning principles. A key element of DDMRP is its inventory replenishment model, which relies on dynamically adjusted inventory buffers rather than fixed stock levels. However, parameterization of these buffers often involves subjective choices, raising concerns about consistency and performance. This paper assesses the DDMRP replenishment model through discrete-event simulation of a multi-echelon, capacity-constrained production system. Two alternative formulations of the safety stock term in the red zone are compared: the original factor-based approach and a revised formula that incorporates measurable variability coefficients. While both safety stock formulations yield similar numerical results, the revised formula enhances transparency and reduces subjectivity. Assessing the impact of introducing a buffer for components in addition to a finished goods buffer further shows that the components buffer can reduce finished goods inventory requirements while maintaining service levels. These findings contribute to a better understanding of the DDMRP replenishment model, offering practical insights for parameter selection and supply chain design.

Authors

Institutions

Publication Details

Journal
Mathematics
Published
2025-10-31
DOI
https://doi.org/10.3390/math13213483
Citations
1
Primary Topic
Supply Chain and Inventory Management
Type
article
Field-Weighted Citation Impact
2.28

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The DDMRP Replenishment Model: An Assessment by Simulation

Matthias Thürer, Paulo Ávila, Luı́s Pinto Ferreira, Nuno Octávio Garcia Fernandes et al.
1 citations
Mathematics
Supply Chain and Inventory Management
2.28
article

The DDMRP Replenishment Model: An Assessment by Simulation

Matthias Thürer, Paulo Ávila, Luı́s Pinto Ferreira, Nuno Octávio Garcia Fernandes, Sílvio Carmo Silva, Suleimane Djabi
article en
1 citations

Abstract

Demand-Driven Material Requirements Planning (DDMRP) has been proposed as a solution for managing uncertainty and variability in supply chains by combining decoupling, buffer management and demand-driven planning principles. A key element of DDMRP is its inventory replenishment model, which relies on dynamically adjusted inventory buffers rather than fixed stock levels. However, parameterization of these buffers often involves subjective choices, raising concerns about consistency and performance. This paper assesses the DDMRP replenishment model through discrete-event simulation of a multi-echelon, capacity-constrained production system. Two alternative formulations of the safety stock term in the red zone are compared: the original factor-based approach and a revised formula that incorporates measurable variability coefficients. While both safety stock formulations yield similar numerical results, the revised formula enhances transparency and reduces subjectivity. Assessing the impact of introducing a buffer for components in addition to a finished goods buffer further shows that the components buffer can reduce finished goods inventory requirements while maintaining service levels. These findings contribute to a better understanding of the DDMRP replenishment model, offering practical insights for parameter selection and supply chain design.

MathematicsVol. 13(21)
Universidade Politécnica de Castelo Branco (PT), Chemnitz University of Technology (DE), Institute of Mechanical Engineering and Industrial Mangement (PT), Institute for Systems Engineering and Computers (PT), INESC TEC (PT), Laboratório Associado de Energia, Transportes e Aeronáutica (PT), Polytechnic Institute of Porto (PT), University of Minho (PT)
Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 8%
Supply Chain and Inventory Management
2.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.