2021
DOI: 10.1007/s40962-021-00680-x
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Sand Casting Implementation of Two-Dimensional Digital Code Direct-Part-Marking Using Additively Manufactured Tags

Abstract: 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 roo… Show more

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Cited by 6 publications
(10 citation statements)
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“…A brief introduction about AM processes and their relation to other manufacturing processes in context of DPMs is given. For DPMs, the main focus of research lies in the conception and production of DPMs mostly using established applications to read codes, while in this approach, the reading process is focused [ 3 , 14 ]. Therefore, image processing techniques are addressed, and especially, DL methods and their performance under data limitation are highlighted.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…A brief introduction about AM processes and their relation to other manufacturing processes in context of DPMs is given. For DPMs, the main focus of research lies in the conception and production of DPMs mostly using established applications to read codes, while in this approach, the reading process is focused [ 3 , 14 ]. Therefore, image processing techniques are addressed, and especially, DL methods and their performance under data limitation are highlighted.…”
Section: Related Workmentioning
confidence: 99%
“…Because of this, a more flexible approach to find and detect data matrix codes is needed. In the context of sand casting, Uyan et al present how direct-part markings can be read with tablets or mobile phones by free bar code readers [ 14 ]. The focus is on the production and analysis of DPMs in the form of data matrix codes and underlines the need for high contrasts for readable tags but, as common bar code readers fail to read DPM on SLS parts, this underlines the need for a novel approach.…”
Section: Related Workmentioning
confidence: 99%
“…A foundry operates under harsh conditions, and it is difficult to track and mark each part from the beginning of input material flow to the final casting component. [1][2][3] The second challenge is to preprocess the time series data into features for machine learning statistical analysis. 4 It is useful not to consider full dataset but rather engineering statistics which are understood by the process engineers.…”
Section: Challenges In Foundry Quality Control and Root Cause Analysismentioning
confidence: 99%
“…The process of creating an AM2D tag and its implementation onto different castings have been studied and compared with methods such as laser marking, pin-type tooling methods, and classical alphanumeric labeling. 5 The DPM created by AM2D tags can be read very early, even at the shakeout before cleaning. The method has been shown for several industrial parts and a foundry part-marking and tracking system has been demonstrated for use in root cause analysis of defects and statistical quality control.…”
Section: Introductionmentioning
confidence: 99%
“…The method has been shown for several industrial parts and a foundry part-marking and tracking system has been demonstrated for use in root cause analysis of defects and statistical quality control. 4,5 Creating a DPM using an AM2D tag involves printing a uniquely coded polymer tag, inserting it into a mold, and then casting the metal part in which the molten metal raises the polymer tag above its ignition temperature and the tag burns away from the mold, leaving an imprinted DPM on the part. A problem with AM2D tags is that it is unclear how thick the metal part must be to raise the polymer to its ignition temperature and burn away the tag and provide a readable DPM.…”
Section: Introductionmentioning
confidence: 99%