Discrete-Event Simulation for Scenario-Based Evaluation of Internal Logistics in Paving Block Production: An Industry 4.0 Perspective

The increasing demand for efficient manufacturing systems in the construction-materials industry creates a need for digital methods that enable logistics alternatives to be evaluated before physical implementation. This study applies discrete-event simulation (DES) to a real concrete paving block production system to evaluate two complementary dimensions of internal logistics improvement: logistics-system reconfiguration and coordinated resource scaling. An empirically parameterized case-study model was developed to represent mixing, vibro-pressing, curing, quality control, packaging, technological-pallet circulation, and internal transport. First, a baseline forklift-based configuration was compared with an improved configuration incorporating partial transport automation and reorganization of curing-zone material flow. In a single deterministic five-day run under identical technological assumptions, cumulative simulated output increased from 1825 to 3141 finished pallets, corresponding to a 72.1% higher output in the improved configuration. This result represents a deterministic case-scenario comparison rather than a replication-based statistical effect estimate. Second, a separate replicated resource-scaling experiment evaluated coordinated changes in forklifts, packing stations, and quality-control units. This experiment was not factorially crossed with the logistics-configuration comparison; therefore, no interaction effect between logistics configuration and resource level is inferred. The model is an offline DES decision-support representation rather than a fully integrated Digital Twin, as it does not include real-time synchronization, automatic state updating, or feedback-based control. The results demonstrate how DES can support scenario-based assessment of logistics redesign and resource-allocation decisions while making explicit the case-specific and methodological limits of the resulting performance estimates.