Cargando…

Motor Power Signal Analysis for End-Point Detection of Chemical Mechanical Planarization

In the integrated circuit (IC) manufacturing, in-situ end-point detection (EPD) is an important issue in the chemical mechanical planarization (CMP) process. In the paper, we chose the motor power signal of the polishing platen as the monitoring object. We then used the moving average method, which...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Hongkai, Lu, Xinchun, Luo, Jianbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6190379/
http://dx.doi.org/10.3390/mi8060177
_version_ 1783363556790501376
author Li, Hongkai
Lu, Xinchun
Luo, Jianbin
author_facet Li, Hongkai
Lu, Xinchun
Luo, Jianbin
author_sort Li, Hongkai
collection PubMed
description In the integrated circuit (IC) manufacturing, in-situ end-point detection (EPD) is an important issue in the chemical mechanical planarization (CMP) process. In the paper, we chose the motor power signal of the polishing platen as the monitoring object. We then used the moving average method, which was appropriate for in-situ calculation process and made it easy to code for software development, to smooth the signal curve, and then studied the signal variation during the actual CMP process. The results demonstrated that the motor power signal contained the end-point feature of the metal layer removal, and the processed signal curve facilitated the feature extraction and it was relatively steady before and after the layer transition stage. In addition, the motor power signal variation of the polishing head was explored and further analysis of time delay was performed.
format Online
Article
Text
id pubmed-6190379
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-61903792018-11-01 Motor Power Signal Analysis for End-Point Detection of Chemical Mechanical Planarization Li, Hongkai Lu, Xinchun Luo, Jianbin Micromachines (Basel) Article In the integrated circuit (IC) manufacturing, in-situ end-point detection (EPD) is an important issue in the chemical mechanical planarization (CMP) process. In the paper, we chose the motor power signal of the polishing platen as the monitoring object. We then used the moving average method, which was appropriate for in-situ calculation process and made it easy to code for software development, to smooth the signal curve, and then studied the signal variation during the actual CMP process. The results demonstrated that the motor power signal contained the end-point feature of the metal layer removal, and the processed signal curve facilitated the feature extraction and it was relatively steady before and after the layer transition stage. In addition, the motor power signal variation of the polishing head was explored and further analysis of time delay was performed. MDPI 2017-06-05 /pmc/articles/PMC6190379/ http://dx.doi.org/10.3390/mi8060177 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Hongkai
Lu, Xinchun
Luo, Jianbin
Motor Power Signal Analysis for End-Point Detection of Chemical Mechanical Planarization
title Motor Power Signal Analysis for End-Point Detection of Chemical Mechanical Planarization
title_full Motor Power Signal Analysis for End-Point Detection of Chemical Mechanical Planarization
title_fullStr Motor Power Signal Analysis for End-Point Detection of Chemical Mechanical Planarization
title_full_unstemmed Motor Power Signal Analysis for End-Point Detection of Chemical Mechanical Planarization
title_short Motor Power Signal Analysis for End-Point Detection of Chemical Mechanical Planarization
title_sort motor power signal analysis for end-point detection of chemical mechanical planarization
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6190379/
http://dx.doi.org/10.3390/mi8060177
work_keys_str_mv AT lihongkai motorpowersignalanalysisforendpointdetectionofchemicalmechanicalplanarization
AT luxinchun motorpowersignalanalysisforendpointdetectionofchemicalmechanicalplanarization
AT luojianbin motorpowersignalanalysisforendpointdetectionofchemicalmechanicalplanarization