The DDMRP Replenishment Model: An Assessment by Simulation

Nuno O. Fernandes (), Suleimane Djabi, Matthias Thürer, Paulo Ávila, Luís Pinto Ferreira and Sílvio Carmo-Silva
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Nuno O. Fernandes: Instituto Politécnico de Castelo Branco, 6000-767 Castelo Branco, Portugal
Suleimane Djabi: Instituto Politécnico de Castelo Branco, 6000-767 Castelo Branco, Portugal
Matthias Thürer: Chair of Factory Planning and Intralogistics, Chemnitz University of Technology, 09111 Chemnitz, Germany
Paulo Ávila: ISEP, Polytechnic of Porto, rua Dr. António Ber-nardino de Almeida, 4249-015 Porto, Portugal
Luís Pinto Ferreira: ISEP, Polytechnic of Porto, rua Dr. António Ber-nardino de Almeida, 4249-015 Porto, Portugal
Sílvio Carmo-Silva: ALGORITMI Research Centre, University of Minho, 4710-057 Braga, Portugal

Mathematics, 2025, vol. 13, issue 21, 1-13

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.

Keywords: safety stock; DDMRP; production planning and control; discrete event simulation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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