Optimizing buffer management strategies for engineer-to-order project supply chains in uncertain environments

Abstract

Engineer-to-Order (ETO) project supply chains exhibit heightened operational complexity due to product customization, geographically dispersed supplier networks, and demand uncertainty. While existing studies have validated the risk-mitigation value of safety stock and time buffers, two critical gaps persist at the micro-operational level: (1) the absence of refined configuration methods for node-specific buffer parameters, and (2) the pressing need for dynamic adjustment mechanisms responsive to real-time disruptions. We propose a cascading risk-driven dynamic buffer management framework for supply chains. First, a multidimensional cascading risk quantification index system is developed, which integrates edge load and risk perception dimensions to precisely identify and quantify risk propagation effects, thereby enabling optimal node-level buffer strategy design. Second, a real-time monitoring-based cross-node buffer resource coordination mechanism is created, enhancing system resilience through dynamic adjustments in buffer capacity and allocation. The simulation results demonstrate that this approach can improve on-time delivery performance and reduce supply chain costs. This research provides a decision support tool for ETO project supply chains to dynamically balance operational resilience and cost efficiency in uncertain environments.