High temperature furnace with controlled atmosphere, data acquisition, and material characterization

奥格斯堡大学材料资源管理研究所(MRM)材料工程教授的一个主要关注点是广泛采用的陶瓷的加工，主要是精确定义和控制工艺参数的非氧化物陶瓷基复合材料的加工。在热处理过程中，应在线测量和检测所有参数和所产生的材料性能，以评估工艺条件对材料性能的影响。对于这种方法，一个配备了传感器和分析仪的高温炉是必要的。所获得的数据将用于高温处理的控制，并与复合材料的力学和物理性能相关联。基于工艺性能相关性，将准确地定义工艺，以优化所制造材料的性能。此外，传感器数据将用于数字材料开发，以便基于原材料和工艺参数预测材料和组件属性。所有实验数据，特别是表征材料成分的在线数据将用于数字材料开发。目的是预测最终复合材料的性能依赖于原材料和相应的工艺参数。如果这是可能的，那么，另一方面，反向材料工程可以进行。此外，这种基于传感器的智能高温处理的科学方法旨在实现复合材料的资源节约化制造。通过性能和生态影响的相关性来评价纤维增强陶瓷的可持续性是可能的。到目前为止，陶瓷基复合材料的制备都着眼于性能的优化。通过这种方法，可以生产出与应用相关的性能、寿命、可回收性、能源和资源消耗都达到最优的资源节约型材料。这种智能制造和相应的工艺参数属性关联允许从资源节约性的角度对陶瓷基复合材料从材料合成到再利用和回收的整个加工链进行评估。

One main focus of the chair of Materials Engineering at the institute of Materials Resource Management (MRM) at University of Augsburg is the processing of well adopted ceramics, mainly nonoxide ceramic matrix composites with precisely defined and controlled process parameters. During thermal processing all parameters and the resulting material properties shall be measured and detected online in order to evaluate the influence of process conditions on the material properties. For this approach a high temperature furnace is necessary which is well equipped with sensors and analytics. The acquired data will be used for control of the high temperature treatment and also correlated with the mechanical and physical properties of the composites. Based on the process property correlation the processing will be accurately defined for optimized properties of the manufactured materials. Additionally, the sensor data will be used for the digital material development in order to predict the material and component properties based on raw materials and process parameters. All experimental data, especially the online data characterizing the material composition will be used for digital material development. Aim is the prediction of properties of the final composite dependent on raw materials and according process parameters. If this is possible then, on the other hand, reverse material engineering can be performed.Additionally, this scientific approach of a sensor based intelligent high temperature processing is aimed to the resource efficient manufacturing of composites. it will be possible to evaluate the sustainability of fiber reinforced ceramics with correlation of properties and ecological impact. So far ceramic matrix composites were manufactured with focus on best properties. With this approach it will be possible to produce resource efficient materials where application relevant properties, lifetime, recyclability, energy and resource consumption are adjusted to a total optimum.This intelligent manufacturing and the according processing parameter property correlation allows the evaluation of the complete processing chain of ceramic matrix composites from the material synthesis to reuse and recycling under resource efficient point of view.