Thermomechanical ring rolling with predictive property control

热机械切向环件轧制（TMR）是一种用于生产近净形环件几何形状的工艺，其通过成形速度和温度的闭环控制来同时有针对性地影响微观结构和硬度。为此，使用PID和预测模型的组合方法，以使用完整的现有工艺窗口，从而同时实现最终几何形状、显微组织和硬度的目标值。在FÖP I和II中，进行了系统架构、所需软传感器和相关模型的开发，以及实时测量数据采集系统的实施，以便在环件轧制机上实现闭环控制。级联控制回路用于控制成形速度和空气流量，并因此控制冷却速率和所得微观结构。在实验测试中，分析了过程变量和干扰变量，表征了它们的影响，并在FÖP II过程中证明了所实施的温度控制回路的有效性。用于微结构开发的软测量结合了温度传感器和项目中开发的涡流传感器，以快速温度、材料和成形模型记录表面上的微结构，以预测环内部的环性能。基于测量数据和预测模型连续调整最佳输入参数。FÖP II的研究结果产生了一个控制环轧机和确定相关工艺窗口的概念，这将在第三个供资期内进行。FÖP III的目标是在接近生产条件下完成控制器的实施。这将有助于识别和量化控制回路对不同配置中过程性能的影响。此外，工艺限度的确定确保了所开发方法的可移植性，例如，不同的环几何形状或材料。 为此，现有的数字孪生模型被扩展以允许对过程进行仿真，包括闭环控制。在真实的机器上验证之后，将能够将针对几何形状和配置的控制策略转移到在现有轧机上不可行的情况。的过程和系统性能的分析将允许推导的设计原则和规则的系统架构（执行器，传感器，建模和控制）的实施热机械控制环轧制。

Thermomechanical tangential ring rolling (TMR) is a process for the production of near-net-shape ring geometries with simultaneous targeted influencing of the microstructure and hardness by closed loop control of the forming speed and temperature. For this, a combined approach of PID and predictive models is used, in order to use the full existing process window in such a way that the target values for final geometry, microstructure and hardness can be achieved simultaneously. In FÖP I and II, the development of the system architecture, the required soft sensors and associated models, as well as the implementation of a real-time capable measurement data acquisition system were carried out in order to realize a closed control loop on the ring rolling machine. Cascaded control loops were used to control the forming speed and air flow and, as a result, the cooling rate and the resulting microstructure. In experimental tests, the process and disturbance variables were analysed and their influence characterized, and the effectiveness of the implemented temperature control loop was demonstrated in the course of FÖP II. The soft sensor for microstructure development combines temperature sensors and an eddy current sensor developed in the project to record the microstructure on the surface with fast temperature, material and forming models to predict the ring properties inside the ring. The optimal input parameters are continuously adjusted based on the measured data and a prediction model. The findings from FÖP II led to a concept for the control of the ring rolling machine and the identification of associated process windows, which will be taken up in the third funding period. The goal in FÖP III is to complete the implementation of the controller under near-production conditions. This will serve to identify and quantify the influence of the control loops on process performance in different configurations. Furthermore, the identification of the process limits ensures the transferability of the developed methodology, e.g., to different ring geometries or materials. For this purpose, the existing digital twin is extended to allow a simulation of the process, including the closed loop control. After validation on the real machine, it will be possible to transfer the control strategy for geometries and configurations to cases that are not feasible on the existing rolling mill. An analysis of the process and system performance will allow the derivation of design principles and rules in terms of system architecture (actuators, sensors, modelling and control) for the implementation of thermomechanically-controlled ring rolling.