Microstructure analysis on complex surfaces enables digital quality control of metal parts
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Springer Science and Business Media LLC
https://doi.org/10.1038/s41524-024-01458-5
https://doi.org/10.1038/s41524-024-01458-5
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Funder: Ministry of Education of Singapore, Official Number: MOE2017-T2-2-119
<jats:title>Abstract</jats:title><jats:p>Critical to the growth of digital manufacturing is the development of rapid yet accurate quality control technologies to assess the microstructure of each metal part produced. Typical surface analysis methods are limited in measurement throughput and impose constraints on maximum area size and surface quality, which enforce the tedious practice of extracting and preparing flat, small-scale samples for microstructure analysis. Here, we propose a new approach based on directional reflectance microscopy (DRM) which can yield part-scale microstructure information nondestructively and on curved, complex surfaces. We demonstrate our approach on the airfoil of a turbine blade and carry out a rigorous error analysis using other samples with variable surface geometry. Our results highlight the potential for part-specific quality control in the context of digital manufacturing.</jats:p>
<jats:title>Abstract</jats:title><jats:p>Critical to the growth of digital manufacturing is the development of rapid yet accurate quality control technologies to assess the microstructure of each metal part produced. Typical surface analysis methods are limited in measurement throughput and impose constraints on maximum area size and surface quality, which enforce the tedious practice of extracting and preparing flat, small-scale samples for microstructure analysis. Here, we propose a new approach based on directional reflectance microscopy (DRM) which can yield part-scale microstructure information nondestructively and on curved, complex surfaces. We demonstrate our approach on the airfoil of a turbine blade and carry out a rigorous error analysis using other samples with variable surface geometry. Our results highlight the potential for part-specific quality control in the context of digital manufacturing.</jats:p>