Selective Laser Melting Based Additive Manufacturing Process Diagnostics using In-line Monitoring Technique and Laser-Material Interaction Model 2024-26-0420

Selective Laser Melting (SLM) has gained widespread usage in aviation, aerospace, and die manufacturing due to its exceptional capacity for producing intricate metal components of highly complex geometries. Nevertheless, the instability inherent in the SLM process frequently results in irregularities in the quality of the fabricated components. As a result, this hinders the continuous progress and wider acceptance of SLM technology. Addressing these challenges, in-process quality control strategies during SLM operations have emerged as effective remedies for mitigating the quality inconsistencies found in the final components. This study focuses on utilizing optical emission spectroscopy and IR thermography to continuously monitor and analyze the SLM process within the powder bed, with the aim of strengthening process control and minimizing defects. Optical emission spectroscopy is employed to study the real-time interactions between the laser and powder bed, melt pool dynamics, material behavior, and energy deposition. In parallel, IR thermography provides temperature gradient mapping and thermal insights during SLM, facilitating the detection of potential thermal irregularities. By employing these diagnostic methods, deviations from anticipated process behavior are identified and classified which can be employed in multi-physics model as input for studying defects and deformation. Real-time data acquisition enables swift detection of anomalies like powder segregation, uneven layer melting, and potential thermal concerns. The insights derived from optical emission spectroscopy and IR thermography are processed and analyzed. This study provides the provides the comprehensive process insights through optical spectroscopy and IR thermography. These advanced diagnostics not only elevate the overall quality of manufactured components but also cut down on post-processing and material wastage, rendering additive manufacturing more efficient and dependable.