We present an integrated digital twin framework for supply chain business processes. The framework models supply chain processes as queueing networks where agents perform tasks on orders flowing through the process. The modeling approach captures the routing dynamics and stochasticity in both the task durations and order arrivals that are observed in practice. The digital replica creates value by providing a flexible digital environment that can be used to evaluate policies, mitigate bottlenecks, quote more accurate lead times, and forecast and mitigate disturbances. The digital twin model is updated in real-time using the live process data. Optimization models can be deployed in either offline or online mode. In the offline mode, a deterministic optimization model is executed using the most-recent system parameters at expectation. In the online mode, the framework creates a stochastic simulation environment where online optimization can be performed in a feedback loop.

我们为供应链业务流程提供了一个集成的数字孪生框架。该框架将供应链流程建模为排队网络，代理在流程中执行订单任务。建模方法捕获了在实践中观察到的任务持续时间和订单到达的路由动态和随机性。数字副本通过提供灵活的数字环境来创造价值，该环境可用于评估政策、缓解瓶颈、报价更准确的交货时间以及预测和减轻干扰。数字孪生模型使用实时过程数据实时更新。优化模型可以离线或在线模式部署。在离线模式下，使用最新的系统参数按预期执行确定性优化模型。