Process twins provide real-time representations of entire production processes. By capturing how process steps interact, rather than monitoring a single machine in isolation as an asset-based digital twin does, they have the potential to drive efficiency gains across the whole process. However, developing a process twin is costly. It requires accurately modelling the entire production process: its process steps, the equipment and product-specific settings each step uses, and its process variations. The resulting model must then be bound to live operational data. We present FacProcessTwin, a system that leverages a large language model (LLM) to reduce this development time, building a process twin from a plant's process documentation and natural-language input from an operator. FacProcessTwin generates this complete process model and then automatically binds its process steps to live operational data. The generated model and its data bindings are rendered as an interactive process diagram through which manufacturing personnel can monitor and correct the system's autonomous decisions, such as resolving uncertainty at safety-critical binding steps. We evaluate FacProcessTwin through a real-world case study of an Australian food manufacturer, covering 16 production process flows that span chilled, frozen, and aseptic shelf-stable product categories and include process variations within the same product. The results show that FacProcessTwin generates these process models accurately (a mean F1 of 95.2% against ground truth) and builds each twin in roughly a sixth of the manual time. Its human-in-the-loop governance then keeps the safety-critical bindings correct: at ambiguous tags where a single-pass baseline silently mis-binds 75.0% of the time, FacProcessTwin defers to the operator and mis-binds none.

翻译：过程孪生提供整个生产过程的实时表示。通过捕捉过程步骤之间的交互，而非像基于资产的数字孪生那样孤立地监控单台设备，它们具有推动整个流程效率提升的潜力。然而，开发过程孪生成本高昂。它需要精确建模整个生产过程：包括其过程步骤、各步骤使用的设备与产品特定设置，以及过程变体。最终生成的模型必须绑定实时运行数据。本文提出FacProcessTwin系统，该系统利用大语言模型缩短开发时间，通过工厂的过程文档和操作员的自然语言输入构建过程孪生。FacProcessTwin生成完整的过程模型，并自动将其过程步骤绑定到实时运行数据。生成的模型及其数据绑定以交互式过程图的形式呈现，制造人员可通过该图监控和纠正系统自主决策（例如解决安全关键绑定步骤中的不确定性）。我们通过一家澳大利亚食品制造商的真实案例研究评估FacProcessTwin，该案例涵盖16条生产过程流，涉及冷藏、冷冻和无菌货架稳定产品类别，并包含同一产品内的过程变体。结果表明，FacProcessTwin准确生成这些过程模型（与真实数据相比，平均F1值为95.2%），且每个孪生的构建时间约为手动时间的六分之一。随后，其人在回路治理机制确保安全关键绑定的正确性：在单次基线处理中75.0%情况下错误绑定的模糊标签处，FacProcessTwin将决策权交予操作员，实现零错误绑定。