Demand-Driven Material Requirements Planning in Downstream Supply Chains: A comprehensive review

Abstract

The current industrial environment is uncertain, characterized by significant variability in demand and lead times. In these conditions, the traditional planning methods are limited. The approach Demand Driven Material Requirements Planning (DDMRP) is based on demand Driven planning and flow management using strategic coupling points. This article presents a synthesis of the literature review of research focusing on two main aspects: down-stream logistics and the application of DDMRP in the supply chain. The objective of this study is to identify the main scientific contributions and to highlight persistent limitations. The reviewed studies indicate that DDMRP can improve product availability, reduce lead times and provide better control of stock levels, which ensures an overall improvement in logistics performance. The perspectives of this study are the validation of these approaches in various industrial contexts, notably the automotive sector. In addition, the integration of advanced technologies, such as artificial intelligence to im-prove analytical capabilities and decision-making processes, in demand-driven logistics systems. This study examines a mathematical approach to sizing buffers in DDMRP, its assumptions, its strengths and its limitations. With the aim of identifying research gaps and potential ideas for improvement. The main contributions of this work include a detailed review of existing DDMRP models, a critical analysis of their limitations notably the use of static assumptions and the lack of validation in real-world scenarios and the incorporation of a mathematical perspective on buffer stock sizing. This study also contributes to identifying key research gaps and demonstrating the potential of artificial intelligence techniques to improve the adaptability of DDMRP, optimize decision-making, and reinforce supply chain resilience.