![](bg8.png)
ing a suitable measure. The performance of similarity
measures may vary depending on different datasets.
In this paper, we studied a quantitative comparison for
different similarity measures on UT images of ingots.
The aim of this study was to clarify which similarity
measures are more appropriate and applicable when
searching for specific ultrasonic patterns. Further, we
conducted interviews with domain experts in the anal-
ysis of UT indications images comparison and used
this feedback to define a ground truth for our eval-
uation. We provided a discussion and demonstrated
the possible insights enabled by our approach and its
potential to support production data exploration.
Future work includes investigation of process data
corresponding to groups of similar ingots and batches,
and potentially discovering key influential parameters
in the process data. As future work, we also want
to include advanced multidimensional data visualiza-
tions, to support pattern detection and parameter cor-
relation. Furthermore, automatic classification of cer-
tain quality patterns, based on interactively provided
expert examples, is considered an interesting future
extension of an existing visual analytics solution.
ACKNOWLEDGEMENTS
This research work is done by Pro2Future and AMAG
Austria Metall AG. Pro2Future is funded within the
Austrian COMET Program-Competence Centers for
Excellent Technologies under the auspices of the Aus-
trian Federal Ministry of Transport, Innovation and
Technology, the Austrian Federal Ministry for Digital
and Economic Affairs and of the Provinces of Upper
Austria and Styria. COMET is managed by the Aus-
trian Research Promotion Agency FFG.
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