With the development of the global multimodal transport system and cross-border e-commerce, instant-delivery networks, and automated scheduling, manual operation of freight handling has been replaced by a digital mode of operation based on real-time event collection, automatic state transitions, and end-to-end traceable process governance. This study proposes new solutions to problems in the traditional transportation management system, such as long-link state consistency, anomaly recovery, cross-entity collaboration and operational visualisation, and builds a distributed workflow engine and state machine processing framework based on freight operations. The four main objects in the framework are waybills, containers, pallets and vehicles; trigger sources are events; and a declarative state machine is used to describe the process. Idempotent control, partitioned scheduling, compensating transactions and observable metrics are used for autonomous operation. Prototype experiments have shown that the above mechanism can reduce the end-to-end state transition time, increase the number of anomaly closures and the proportion of automated execution, and maintain good throughput after partition expansion. Based on the above research results, a platform that can be run by freight companies for automated operations has been constructed.

Haoran Xin, Freight Operation Automation and State-Machine Processing Mechanism Based on a Distributed Workflow Engine. International Journal of Social Sciences and Economic Management (2026), Vol. 7, Issue 2: 46-57. https://doi.doi.org/10.3807/IJSSEM.2026.070205.

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