More insight with image processing

A large number of different disruptive phenomena such as melting bath turbulence, welding fume formation, spatter or other anomalies make it difficult to monitor and control PBLM processes. © Aconity3D

The image data provided by the cameras gives the experts at Aconity3D additional insights into the PBLM process, explains Lübbert: "With these high-speed cameras, we can, for example, compare contour scans of material layers across the build process and observe the behavior of the molten pool in critical component areas. In this way, we can identify defects such as melt pools breaking off or inhomogeneous surface conditions. This makes it possible to recognize the influence of changing laser parameters such as modulation frequency and modulation length on the size of the melt pool if all other laser parameters remain constant. The data obtained in this way can be used to expand our knowledge of PBLM processes and isolate the underlying effects." In combination with other measurement methods such as pyrometry, the knowledge gained in this way forms the basis for more efficient materials research in the field of 3D metal printing.

The inline inspection method has the potential to detect production defects at an early stage. This results in a lower number of destructive material tests and lower manufacturing costs. In addition, reliable process monitoring with a conclusive correlation between the process parameters used and the resulting component properties is a prerequisite for closed-loop process control. Such control systems have been used for conventional laser welding processes for many years. "In PBLM processes, however, process monitoring or even process control is still at a very early technological stage, but our developments are helping to reduce this backlog," says Lübbert.

The main obstacle to inline process monitoring and control of PBLM processes is the transient nature of the process, which is determined by phenomena such as melt pool turbulence, welding fume formation, spatter or other anomalies in the powder bed. These underlying disturbing process phenomena increase the measurement noise and reduce the accuracy of the information that can be obtained directly from the melt pool.

The Mikrotron high-speed camera used is a good choice for this application for several reasons, explains Karl Laderer, Area Sales Manager DACH, who is responsible for sales of the Mikrotron product range: "The high-speed camera has a sensor that allows the region of interest (ROI) to be scaled in both the Y and X directions. The special feature of this sensor is that the frame rate can be increased by reducing the number of pixels in the X direction. In this way, small ROIs with a high frame rate can be realized, which gives users enormous flexibility to adapt the camera to the requirements at hand." According to Laderer, the pixel size of 8 µm× 8 µm of the 3 MP sensor and the fanless design for easy integration are also important camera features that ensure reliable results when monitoring PBLM processes. The inline process monitoring tool developed by Aconity3D is available for almost all of the company's systems, for example for the entry-level AconityMini system and the currently largest AconityTwo system with optional multi-laser setup. The target group for these systems are research institutes and the research departments of large companies involved in PBLM processes.

Product Manager Lutz Lübbert summarizes: "Process monitoring using high-speed vision systems is an effective tool to learn more about the running mechanisms and to improve the quality of parts during production instead of analyzing the finished parts for later parameter optimization. Our goal is to advance the development of detection algorithms that can quickly and reliably identify excessive melt pool sizes in order to initiate immediate countermeasures. Based on our positive experience with the products we have used so far and the helpful support we have received, including in programming issues, I also see the high-speed cameras from SVS-Vistek as essential components for our future systems."