Advanced CMP Process Control by Using Machine Learning Image Analysis

Autor:	Chih-Chen Lin, Tuung Luoh, Min-Hsuan Hsu, Ling-Wuu Yang, Kuang-Chao Chen, Hsiang-Meng Yu, Tahone Yang, Kuang-Wei Chen
Rok vydání:	2021
Předmět:	Materials science business.industry Process (computing) Semiconductor device modeling NAND gate Polishing Hardware_PERFORMANCEANDRELIABILITY Edge (geometry) Machine learning computer.software_genre Grayscale Hardware_INTEGRATEDCIRCUITS Process control Wafer Artificial intelligence business computer
Zdroj:	2021 IEEE International Interconnect Technology Conference (IITC).
Popis:	Chemical-mechanical polishing closed loop control optimized process with machine learning assisted wafer image analysis algorithm implemented on the inter layer dielectric of 3D NAND ON stacking with poly-silicon stop layer is studied. The grayscale wafer image can be responded for film residue, stop layer damage, wafer edge damage, and thickness variation. Polishing five zones control model is trainned with wafer grayscale value by Python NN model with two hidden layers. The best condition of closed loop feedback control is deduced by machine learning assisted wafer image analysis algorithm.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::113c38825c6630b831f416cd94218873 https://doi.org/10.1109/iitc51362.2021.9537421 Zobrazit plný text záznamu