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Journal Article

Feature Selection for Troubleshooting in Complex Assembly Lines

MPS-Authors
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Schölkopf,  B
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Resource

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4266824
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Citation

Pfingsten, T., Herrmann, D., Schnitzler, T., Feustel, A., & Schölkopf, B. (2007). Feature Selection for Troubleshooting in Complex Assembly Lines. IEEE Transactions on Automation Science and Engineering, 4(3), 465-469. doi:10.1109/TASE.2006.888054.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-CC99-B
Abstract
The final properties of sophisticated products can
be affected by many unapparent dependencies within the manufacturing
process, and the products’ integrity can often only be
checked in a final measurement. Troubleshooting can therefore
be very tedious if not impossible in large assembly lines.
In this paper we show that Feature Selection is an efficient tool for
serial-grouped lines to reveal causes for irregularities in product
attributes. We compare the performance of several methods for
Feature Selection on real-world problems in mass-production of
semiconductor devices.
Note to Practitioners— We present a data based procedure
to localize flaws in large production lines: using the results of
final quality inspections and information about which machines
processed which batches, we are able to identify machines which
cause low yield.