Performance improvement of a laser cladding system through FPGA-based control

Industrial Laser Cladding Systems: FPGA-Based Adaptive Control

“…As experimentally demonstrated in [11], this approach performs significantly better than the existing PCbased solutions, particularly when targeting short or narrow areas or complex geometries (found in many practical applications), for which PC-based solutions are not suitable because of their low speed and large settling time. However, some practical problems and issues still affect this static solution.…”

“…First, process monitoring was enhanced by using a vision system based on a CMOS camera and an FPGA-based image-processing system [9], which was later further improved in terms of its robustness to optical defects [10]. The FPGA system was then extended to incorporate a digital PI controller [11]. Both the monitoring and control systems presented in [9]- [11] outperformed the preexisting ones used in the industry and overcame some of their limitations.…”

“…The FPGA system was then extended to incorporate a digital PI controller [11]. Both the monitoring and control systems presented in [9]- [11] outperformed the preexisting ones used in the industry and overcame some of their limitations. However, having a fixed control structure presents some practical limitations.…”

Augmented Reality, Cyber-Physical Systems, and Feedback Control for Additive Manufacturing: A Review

“…Processing algorithms can also be employed to increase the robustness of monitoring [135]. Taking advantage of this FPGA-based monitoring, a PI controller has been developed in [136] for controlling the melt pool depth. Subsequent experimental results demonstrate a significant performance improvement of the FPGA-based solution when compared to existing PC-based solutions.…”

Latest Developments in Industrial Hybrid Machine Tools That Combine Additive and Subtractive Operations

“…As far as DED processes are concerned, temperature monitoring is of major importance, as the melt pool temperature is a relevant parameter that affects both the metallurgical quality and geometry accuracy of the manufactured component [123]. In addition, the height of the layers consequently, the quality of the deposition [124,125]. Hofman et al developed feedback control algorithms that enable to adjust process parameters in situ in order to control the melt pool size [126] and measure the clad height in real time [127,128].…”