Quality control using scalar quality measures is standard practice in manufacturing. However, there are also quality measures that are determined at a large number of positions on a product, since the spatial distribution is important. We denote such a mapping of local coordinates on the product to values of a measure as a measurement map. In this paper, we examine how measurement maps can be clustered according to a novel notion of similarity - mapscape similarity - that considers the overall course of the measure on the map. We present a class of synopses called global slope change that uses the profile of the measure along several lines from a reference point to different points on the borders to represent a measurement map. We conduct an evaluation of global slope change using a real-world data set from manufacturing and demonstrate its superiority over other synopses.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:81358 |
Date | 01 November 2022 |
Creators | Lehner, Wolfgang, Rosenthal, Frank, Fischer, Ulrike, Volk, Peter B. |
Publisher | IEEE |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/acceptedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
Relation | 978-1-4244-5242-2, 10.1109/ICDM.2009.117 |
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