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Methodology for Assessing Measurement Error for Casting Surface Inspection
Author(s) -
Gokcer Daricilar,
F. E. Peters
Publication year - 2011
Publication title -
international journal of metalcasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.475
H-Index - 19
eISSN - 2163-3193
pISSN - 1939-5981
DOI - 10.1007/bf03355514
Subject(s) - repeatability , reproducibility , visual inspection , process (computing) , retraining , computer science , a priori and a posteriori , variance (accounting) , task (project management) , casting , reliability engineering , artificial intelligence , materials science , statistics , mathematics , engineering , systems engineering , philosophy , accounting , epistemology , international trade , business , composite material , operating system
Visual assessment of objects is critical to many fields including metalcasting. While the output for such a task is often a simple attribute, the problem studied here is for inspection tasks requiring an output that defines shape, size and location of anomalous areas, which are random and are not defined a priori. This paper defines a methodology to quantify the amount of repeatability and reproducibility variation. The application of the methodology for the visual surface assessment of steel castings reveals significant repeatability and reproducibility error. The work presented here is the impetus for current efforts that are defining the capabilities of the visual inspection process and ways to improve it through the selection, training and retraining of operators and through better control of the process.

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