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Computer‐Assisted Colorimetric Optical Texture Analysis for Ceramic Injection Molding Components
Author(s) -
Gadow R.,
Lischka M.,
Fischer R.
Publication year - 2005
Publication title -
international journal of applied ceramic technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.4
H-Index - 57
eISSN - 1744-7402
pISSN - 1546-542X
DOI - 10.1111/j.1744-7402.2005.02030.x
Subject(s) - materials science , ceramic , texture (cosmology) , molding (decorative) , composite material , raw material , computer science , artificial intelligence , chemistry , image (mathematics) , organic chemistry
In forming and shaping processes with thermoplastic feedstocks e.g., as in ceramic injection molding, (CIM) the formation of textures is observed. These frozen flow structures are dependent on the rheological properties of the feedstock, geometric factors of the mold, and CIM parameters such as injection velocity, pressure, temperature, etc. The effects of these textures on the mechanical properties of the components produced have to be analyzed and quantified in order to reach high quality and reliability standards. The analytical methods need to be exact and reliable to control and optimize the manufacturing process. In this work, optical texture analysis coupled with electronic color‐data processing high‐resolution image analysis is described. The method takes advantage of the optical anisotropy of ceramic materials such as alumina, zirconia, etc. Thin sections of sintered alumina components were prepared and analyzed by polarized light microscopy. Since the crystal structure of alumina is anisotropic in shape and light refraction, the orientation of the crystals in the sintered component can be seen as optical interference colors in the thin section and its crystal arrangement. This information about the local orientation is automatically monitored and evaluated by electronic image processing based on the standardized CIELAB palette. Based on this information a prediction of the mechanical properties of components can be made, and optimization of mold design and feedstock composition may be initiated on this database.