Development of an intelligent Digital Twin for prediction and control of the process behavior via transient flowsheet simulation using the example of fluidized bed spray granulation

以流化床喷雾造粒为例，通过瞬态流程图模拟开发智能数字孪生，用于预测和控制过程行为

• 批准号: 460241719
• 负责人: Professor Dr.-Ing. Stefan Heinrich
• 金额: --
• 依托单位: Institut für Feststoffverfahrenstechnik und Partikeltechnologie V-3
• 依托单位国家: 德国
• 项目类别: Research Grants (Transfer Project)
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/460241719?language=en
• 关键词: Development; intelligent; Digital; Twin; prediction

The process monitoring and control of production plants comes along with the ongoing demand for new developments to avoid unwanted process states and sub-specification production charges even though the processes in the field of particle technology have been used in industry for many decades. The main aim of this transfer project is increasing the efficiency of processes from chemical engineering by the development of an intelligent Digital Twin. This will be demonstrated using the example of the fluidized bed spray granulation process. The Digital Twin reproduces the state of the physical plant and predicts its future behavior, enable reliable control of the process. The intelligence of the Digital Twin is defined by the underlying models, which will be obtained by comprehensive data acquisition with continuous offline and online analysis methods. The high attention to detail of the models result in decision recommendations available faster the real-time, which allows predictions as well as process optimization steps. This is developed as a process-specific knowledge module that calls a flowsheet module, calibrates and consolidates the data. The results of the simulations are interpreted by soft sensors. A communication gateway will be developed that is responsible for the interaction between the simulation results and the digital process picture. The fluidized bed spray granulation model will be developed by experiments with a lab-scale plant at Hamburg University of Technology by application of statistical design of experiments. Unwanted process conditions will be deliberately adjusted in order to define the borders of stable process operation. The resulting model is implemented in the flowsheet simulation software Dyssol which has been developed during the DFG predecessor project (SPP 1679). By applying this software tool, the development procedure of the Digital Twin can be easily transferred to other processes and process chains of solids process engineering with minimal effort.Based on the future process states derived by the simulations, recommendations for actions will be implemented into the process control system of the plant. An optimization algorithm determines those parameters that result in a stable operation. The implementation into the process control system is conducted at the industrial partner, the company Pergande Group. Besides the operation of lab-scale plants, the transferability to larger plants will be demonstrated. The extension of current assistant systems will result in a competitive advantage for the distribution of new plants and is a unique feature in the field of fluidized bed technology for the industrial partner. In addition, it is assumed that the efficiency in the field of contract manufacturing can be increased by about 15 % due to a higher availability of the plants.

生产工厂的过程监测和控制伴随着对新开发的持续需求，以避免不必要的过程状态和次要的生产费用，尽管颗粒技术领域的过程已经在工业中使用了几十年。这一转移项目的主要目的是通过开发智能数字双胞胎来提高化工过程的效率。这一点将用沸腾床喷雾造粒过程的例子来演示。Digital Twin再现物理工厂的状态并预测其未来的行为，从而实现对过程的可靠控制。数字双胞胎的智能由底层模型定义，这些模型将通过连续的离线和在线分析方法通过全面的数据采集获得。对模型细节的高度关注使得决策建议可以更快地实时获得，这使得预测和过程优化步骤成为可能。这是作为特定于流程的知识模块开发的，它调用流程图模块、校准和合并数据。仿真结果用软测量进行了解释。将开发一个通信网关，负责模拟结果与数字过程图之间的交互。应用统计设计的方法，在汉堡工业大学的实验室规模装置上进行实验，建立了流态化喷雾造粒模型。将刻意调整不需要的工艺条件，以确定稳定工艺运行的边界。所得到的模型在DFG前身项目(SPP1679)期间开发的流程图模拟软件Dyssol中实现。通过应用该软件工具，Digital Twin的开发过程可以很容易地转移到固体过程工程的其他过程和过程链中，并根据模拟得出的未来过程状态，将行动建议落实到工厂的过程控制系统中。优化算法确定导致稳定运行的那些参数。过程控制系统的实施是在工业合作伙伴Pergande Group公司进行的。除了实验室规模的工厂运行外，还将演示向更大工厂转移的可能性。现有辅助系统的扩展将为新工厂的分布带来竞争优势，这是工业合作伙伴在沸腾床技术领域的一个独特特点。此外，假设由于工厂的可用性更高，合同制造领域的效率可以提高约15%。