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Abstract

Defects affect the properties and behavior of the casting during its service life. Since the defects can occur due to different reasons, they must be correctly identified and categorized, to enable applying the appropriate remedial measures. several different approaches for categorizing casting defects have been proposed in technical literature. They mainly rely on physical description, location, and formation of defects. There is a need for a systematic approach for classifying investment casting defects, considering appropriate attributes such as their size, location, identification stage, inspection method, consistency, appearance of defects. A systematic approach for categorization of investment casting defects considering multiple attributes: detection stage, size, shape, appearance, location, consistency and severity of occurrence. Information about the relevant attributes of major defects encountered in investment casting process has been collected from an industrial foundry. This has been implemented in a cloud-based system to make the system freely and widely accessible.
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