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Statistical quality control is used in foundries to identify special cause defects and root causes by correlating process input variations with casting defects. A difficulty exists in associating process data collected with individual cast parts as the parts are processed through the foundry and then out into the supply chain. Typically, alphanumeric labels for marking castings and manual identification of the castings with route-paper based tracing approaches have been used. Such manual-based systems make root cause analysis of quality defect issues tedious. This study presents the development of a semi-automated approach using 3D printed sand mold inserts shaped as 2D matrix codes which thereby permit directly cast identification code into the parts. This enables automated part tracking at the very beginning of the casting process including mold making. Automated scan based tracking of parts through a foundry and subsequent supply chain allows for statistical process data collected to also be associated with each part processed with unique identification, building upon the part history and pedigree.
- matrix codes
FingerprintDive into the research topics of 'Sand Casting Implementation of Two-Dimensional Digital Code Direct-Part-Marking Using Additively Manufactured Tags'. Together they form a unique fingerprint.
- 1 Active
01/09/2017 → 31/12/2021
Project: Academy of Finland: Other research funding