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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6190379/ http://dx.doi.org/10.3390/mi8060177 |
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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 |