Machine learning-driven multi-objective parameter optimization for sustainable, efficient, and high-quality ultrasonic wire bonding.
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| Title: | Machine learning-driven multi-objective parameter optimization for sustainable, efficient, and high-quality ultrasonic wire bonding. |
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| Authors: | Buchner, Christoph1,2 (AUTHOR) christoph.buchner@strama-mps.de, Riedle, Benjamin1 (AUTHOR) benjamin.riedle@strama-mps.de, Krauß, Jonas3 (AUTHOR) jonas.krauss@ipa.fraunhofer.de, Seidler, Christian T.4 (AUTHOR) christian.seidler@ipa.fraunhofer.de, Huber, Marco F.2,5 (AUTHOR) marco.huber@ieee.org, Eigenbrod, Hartmut5 (AUTHOR) hartmut.eigenbrod@ipa.fraunhofer.de, von Ribbeck, Hans-Georg6 (AUTHOR) hans-georg.vonribbeck@de.fkdelvotec.com, Schlicht, Franz6 (AUTHOR) franz.schlicht@de.fkdelvotec.com |
| Source: | Journal of Intelligent Manufacturing. Apr2026, Vol. 37 Issue 4, p1681-1699. 19p. |
| Database: | Business Source Ultimate |
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| ISSN: | 09565515 |
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| DOI: | 10.1007/s10845-025-02615-3 |
