In situ monitoring of direct energy deposition via structured light system and its application in remanufacturing industry

The direct energy deposition (DED) process utilizes laser energy to melt metal powders and deposit them on the substrate layer to manufacture complex metal parts. This study was applied as a remanufacturing and repair process to fix used parts, which reduced unnecessary waste in the manufacturing industry. However, there could be defects generated during the repair, such as porosity or bumpy morphological defects. Traditionally the operator would use a design of experiment (DOE) or simulation method to understand the printing parameters’ influence on the printed part. There are several influential factors: laser power, scanning speed, powder feeding rate, and standoff distance. Each DED machine has a different setup in practice, which results in some uncertainties for the printing results. For example, the nozzle diameter and laser type could be varied in different DED machines. Thus, it was hypothesized that a repair could be more effective if the printing process could be monitored in real time. In this study, a structured light system (SLS) was used to capture the printing process’s layer-wise information. The SLS system is capable of performing 3D surface scanning with a high resolution of 10 μm. It can provide the information to determine how much material needs to be deposited and monitor the layer-wide surface topography for each layer in real-time. Once a defect was found in situ, the DED machine (hybrid machine) would change the tool and remove the flawed layer. After the repair, the nondestructive approach computed tomography (CT) was applied to examine its interior features. In this research, a DED machine using 316L stainless steel was used to perform the repairing process to demonstrate its effectiveness. The lab-built SLS system was used to capture each layer’s information, and CT data was provided for the quality evaluation. The novel manufacturing approach could improve the DED repair quality, reduce the repair time, and promote repair automation. In the future, it has a great potential to be used in the manufacturing industry to repair used parts and avoid the extra cost involved in buying a new part.