Integrating Disruption Propagation and Buffer Allocation in Smart City Manufacturing Clusters: A Transport-Energy Performance Model for Intermodal Supply Chains

This study integrates disruption propagation and inventory buffer allocation into a unified analytical framework and develops a transport-energy performance model (TEPM) for intermodal supply chains operating within smart city manufacturing clusters (SCMCs). The analyzed system consists of a single intermodal logistics node (ILN), a city logistics node (CLN), and multiple manufacturing buildings, forming a multi-layer network with strong interdependencies between transport, logistics, and production processes. Disruptions may occur at different system layers, including the ILN, transport links, the CLN, and manufacturing entities, and propagate downstream through the network (ripple effect), affecting material availability and production continuity. The proposed model employs the multi-layer Bayesian network method (MLBNM) to represent disruption propagation and interdependencies between system components under uncertainty. Inventory buffers at the CLN and manufacturing nodes are incorporated as decision variables and act as key mitigation mechanisms, enhancing system resilience. Buffer allocation also affects transport-energy performance through its interaction with transport activity and production continuity, linking inventory-based resilience with the energy requirements of material transport. The model integrates network structure, disruption propagation, and inventory-based decision-making into a unified framework. A scenario-based analysis evaluates system performance under different disruption conditions and buffer allocation strategies using a representative SCMC configuration. The results for the analyzed scenarios show how buffer placement and supply chain configuration affect resilience and transport-energy performance within the modeled system. The proposed approach provides a framework for jointly analyzing probabilistic disruption propagation, inventory-based mitigation, and transport-energy performance in intermodal SCMC supply chains.