Cold spraying (CS) is a solid-state coating technique that has been applied as a novel additive manufacturing (AM) method to fabricate freestanding metal components. Recent advances in cold spray additive manufacturing (CSAM) technology call for new process implementation to improve manufacturing accuracy and flexibility. In this study, a concept of modular systems is presented to design and implement a new CSAM framework. The current CSAM system is an open framework system composed of different modules. The flow of the proposed CSAM system is explained to understand the physical and functional relationships between the key elements of the entire system. This physical and functional modularity is useful to promote hybrid AM processes. In addition, based on the smart manufacturing concept of Industry 4.0, a novel approach is proposed to bring the perception and the decision-making abilities into the traditional CS system. Here, a 3D profiler is used to measure the morphology of deposited coatings online and to transfer data to the robot controller. The developed algorithm compares the obtained results with a theoretical model to ensure an adaptive adjustment of the robot trajectory. The experimental validation shows that this approach achieves closed-loop control for CSAM with high-precision by optimizing kinematic parameters in real time.

冷喷涂（CS）是一种固态涂层技术，已被用作一种新颖的增材制造（AM）方法来制造独立式金属部件。冷喷涂增材制造（CSAM）技术的最新进展要求采用新工艺来提高制造精度和灵活性。在这项研究中，提出了模块化系统的概念，以设计和实现新的CSAM框架。当前的CSAM系统是一个由不同模块组成的开放框架系统。说明了提出的CSAM系统的流程，以了解整个系统关键元素之间的物理和功能关系。这种物理和功能模块化对促进混合AM过程非常有用。此外，基于工业4.0的智能制造概念，提出了一种新颖的方法来将感知和决策能力带入传统的CS系统。在这里，使用3D轮廓仪在线测量沉积的涂层的形态并将数据传输到机器人控制器。所开发的算法将获得的结果与理论模型进行比较，以确保对机器人的轨迹进行自适应调整。实验验证表明，该方法通过实时优化运动学参数实现了对CSAM的高精度闭环控制。所开发的算法将获得的结果与理论模型进行比较，以确保对机器人的轨迹进行自适应调整。实验验证表明，该方法通过实时优化运动学参数实现了对CSAM的高精度闭环控制。所开发的算法将获得的结果与理论模型进行比较，以确保对机器人的轨迹进行自适应调整。实验验证表明，该方法通过实时优化运动学参数实现了对CSAM的高精度闭环控制。