Autonomous and self-adapting, high-resolution 3D additive manufacturing by high energy impacts of fine particles

基于冷喷涂的增材制造工艺的可用性和效率关键取决于颗粒在冲击时所达到的速度和温度，因为这些是在部件的成形层上成功沉积的主要因素。因此，它们为整个控制系统定义了所需的过程条件窗口。在这方面，存在两大挑战。第一个挑战是，在冲击时实现的颗粒速度和温度强烈地取决于可能变化的颗粒原料和工艺链中的其他不可预见的变化/干扰。第二个挑战是，上述所需的工艺条件窗口随原材料而变化。为了解决第一个问题，将研究基于模型的控制概念。第二个挑战将通过开发一个基于实时优化的高级控制器来解决，该控制器允许在常规工艺操作期间适应所需的工艺条件窗口。设想的分层控制方案旨在实现基于自动冷喷涂的增材制造，该增材制造对给定颗粒材料（化学成分，导热系数，尺寸和形状分布）的变化具有鲁棒性。实验验证的概念，使用高速粒子图像测速仪，温度场测量和分析所产生的新材料层将进行。

The usability and efficiency of cold-spray based additive manufacturing processes depend crucially on the achieved velocities and temperatures of the particles on impact, as these are the main factors for a successful deposition on the forming layer of the component. Therefore, they define the desired window of process conditions for the overall control system. Here, two major challenges exist. The first challenge is that the achieved particle velocities and temperatures on impact strongly depend on the possibly varying particulate raw material and other unforeseen variations/disturbances in the process chain. The second challenge is that the aforementioned desired window of process conditions varies with the raw material. To solve the first problem model-based control concepts will be investigated. The second challenge will be met by developing a real-time optimization-based high-level controller, which allows for an adaptation of the desired window of process conditions during regular process operation.The envisaged hierarchical control scheme aims for autonomous cold spray based additive manufacturing robust with respect to variations in the given particulate material (chemical composition, thermal conductivity, size and shape distribution). Experimental validation of the concepts using high-speed particle image velocimetry, temperature field measurements and analysis of the produced new material layers will be performed.