In-process adaptive dimension correction strategy for laser aided additive manufacturing using laser line scanning

Abstract

Additive manufacturing (AM) technologies have seen rapid growth in the past decade. Achieving high-quality consistency and accuracy remains a challenge in the fabrication of large-format metallic parts using the directed energy deposition AM processes. An efficient dimension correction strategy is required to prevent build failure during the AM process. In this paper, a laser line scanning sensor was integrated into a robot-based laser aided additive manufacturing (LAAM) system to realise the on-machine measurement of the part geometry. With this system, an in-process adaptive dimension correction strategy was proposed. The dimensional deviations in the intermediate layers could be corrected immediately after they were detected during the LAAM process, thus avoiding excessive dimensional deviation leading to build failure. A tool-path generation process for dimension correction was proposed which did not rely on traditional time-consuming CAD reconstruction. Only 3D point cloud was used directly, enabling the quick response of the LAAM system in restoring the dimensional accuracy. The deviated surface could be automatically filled up, and the subsequent deposition processes were resumed after each cycle of the dimension correction. To facilitate the proposed dimension correction strategy, a Robot Operating System (ROS)-based software platform was developed. Experimental comparisons between the part built with and without correction were conducted. The results demonstrated a significant improvement in dimensional accuracy when the correction strategy was applied.