As one of the most novel additive manufacturing methods, currently selection and optimization of processing parameters in additive friction stir deposition (AFSD) have mainly relied on experiments and subsequent characterization of microstructural and mechanical properties. Such approaches are both time- and resource-consuming. Therefore, an ultrasound elastography enhanced gradient process parameter optimization method was applied in the present work to obtain a window of optimized processing parameters for AFSD processing of aluminum alloy by varying both rotational and linear deposition speeds. The quality of AFSD processed layer was investigated for physical nature of surface, dynamic elastic modulus, and microstructural aspects in cross-sections of the deposited layer. The efficiency in exploring process parameters was significantly enhanced by implementing a high-throughput screening experimental design based on application of gradient process parameters and continuous ultrasound elastographs. In addition, the applied ultrasonic elastography technique assisted in evaluating the homogeneity in microstructure and mechanical properties of AFSD sample over the entire gradients of the process parameters. The techniques adopted in current work can be further extended to identify suitable parameters for AFSD fabrication of components with desired mechanical properties such as hardness, fatigue, etc.

作为最新颖的增材制造方法之一，目前增材搅拌摩擦沉积（AFSD）工艺参数的选择和优化主要依赖于实验和随后的微观结构和机械性能表征。这些方法既费时又费资源。因此，在本工作中应用超声弹性成像增强梯度工艺参数优化方法，通过改变旋转和线性沉积速度来获得铝合金AFSD加工的优化工艺参数窗口。研究了 AFSD 处理层的质量，包括表面物理性质、动态弹性模量以及沉积层横截面的微观结构。通过实施基于梯度工艺参数和连续超声弹性图应用的高通量筛选实验设计，显着提高了探索工艺参数的效率。此外，所应用的超声弹性成像技术有助于评估 AFSD 样品在整个工艺参数梯度上的​​微观结构和机械性能的均匀性。当前工作中采用的技术可以进一步扩展，以确定用于 AFSD 制造具有所需机械性能（如硬度、疲劳等）的部件的合适参数。