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Drill-down analysis with equipment health monitoring

Presentation held at 16th European Advanced Process Control and Manufacturing Conference, APCM 2016, April 11 - 13, 2016, Reutlingen, Germany
: Krauel, Christopher; Weishäupl, Laura; Pfeffer, Markus

Präsentation urn:nbn:de:0011-n-3936299 (1.0 MByte PDF)
MD5 Fingerprint: c8c84563c18fe2d1162c8be96b233d96
Erstellt am: 19.5.2016

2016, 26 Folien
European Advanced Process Control and Manufacturing Conference (APCM) <16, 2016, Reutlingen>
Vortrag, Elektronische Publikation
Fraunhofer IISB ()
monitoring; Equipment Health Factor (EHF); semiconductor; condition monitoring; key feature extraction

This presentation deals with a procedure to track the current equipment state and to identify underperforming parameters. The approach concentrates on the autonomous classification of different process variable types which are defined by particular variable behaviors and the investigation of specified statistical feature extraction methods for every respective class. Also the computation of the Equipment Health Factor (EHF) is presented. The expected benefit of the implementation of an EHF application is the optimization of lot and wafer measurement sampling.