Temperature measurement is essential in metal additive manufacturing, as the spatio-thermal profile strongly influences the microstructure and therefore the key mechanical properties of the produced components. Conventional infrared thermography is widely used for in-situ temperature monitoring. However, its quantitative interpretation is often limited by the varying and generally unknown emissivity of the metal surfaces throughout the build process. This paper presents a pipeline that combines visual and infrared imaging to obtain more physically consistent temperature fields under spatially varying emissivity conditions. A high-resolution visual imaging method is used to segment optically distinguishable process regions. These segmented regions are subsequently mapped onto the corresponding infrared images to enable region-specific effective emissivity settings, resulting in emissivity-corrected temperature fields for surfaces above approximately 600 K. The workflow is demonstrated using a laser beam directed energy deposition system and assessed by comparison with the expected solidification behavior of AISI 316L. The results indicate improved physical consistency compared with a globally fixed emissivity assumption, rather than providing an independent metrological validation of absolute temperature accuracy. Although the workflow requires careful system integration and calibration to account for process-specific factors, it provides an approach that can be adapted to other additive manufacturing systems after appropriate modifications. This supports improved process monitoring and may facilitate the development and validation of predictive process models for metal additive manufacturing.
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Sommerlade et al. (2026) studied this question.
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