CMP Process Optimization Engineering by Machine Learning

Advanced Chemical-mechanical polishing (CMP) process not only needs to maintain stable run-to-run thickness control but also achieve better within wafer/within chip planarization performance. Furthermore, slurries or other consumable parts, like PAD and Disks selection are also the keys for CMP proc...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on semiconductor manufacturing 2021-08, Vol.34 (3), p.280-285
Hauptverfasser:	Yu, Hsiang-Meng, Lin, Chih-Chen, Hsu, Min-Hsuan, Chen, Yen-Ting, Chen, Kuang-Wei, Luoh, Tuung, Yang, Ling-Wuu, Yang, Tahone, Chen, Kuang-Chao
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms artificial intelligence Artificial neural networks Chemical-mechanical polishing closed loop systems Disks Layout Layouts Machine learning Neural networks Optimization Prediction algorithms Predictive models Process control Semiconductor device modeling Semiconductor process modeling Slurries Test vehicles thickness control Topology Wafers
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!