Digital twin technology has been increasingly applied to improve business process management in manufacturing. A first-level digital twin methodology (process simulation model) was tested using the example of a sugar factory acceptance workshop, where the initial processing of sugar beets and their preparation for further processing occur. Digital twins enable enterprises to conduct virtual modeling and testing of new production concepts, optimize processes, predict equipment failures, diagnose production processes using virtual replicas, and improve management methods. The creation of a digital twin for the sugar beet acceptance process allowed for the determination of the process qualitative characteristics. As the process is linear, the throughput of the workshop is determined by the uniform distribution of workload across the entire circuit. A “bottleneck” in the system is defined by an operation that takes more time relative to the preceding and subsequent operations, which creates a queue of transactions. Analysis of the model run revealed “bottlenecks” in the network, specifically, increased queues of trucks at the sugar beet acceptance operation, at the gross weight weighing station, and at the factory entry checkpoint. To address this problem, the system parameters were optimized, with the aim of balancing the load on the nodes of the sugar beet acceptance workshop and reducing queues at the servicing devices (system nodes). The optimization experiment indicated that it is necessary to increase the number of control checks of the beet mass to three and that the loading speed of a truck should be six minutes. As a result, the generalized (averaged) load function on the workshop was reduced by almost a factor of two.