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http://hdl.handle.net/123456789/25077
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DC Field | Value | Language |
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dc.contributor.author | R Shuaimi | - |
dc.contributor.author | R C Ismail | - |
dc.contributor.author | M N Hazwan Hadzir | - |
dc.contributor.author | M N M Isa | - |
dc.contributor.author | A B Jambek | - |
dc.date.accessioned | 2021-08-11T05:45:46Z | - |
dc.date.available | 2021-08-11T05:45:46Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Shuaimi, R., Ismail, R.C., Hazwan Hadzir, M.N., Isa, M.N.M., Jambek, A.B. Investigation of Scribing Quality Defect of Thin Film Solar Cell Using Machine Vision (2020) IOP Conference Series: Materials Science and Engineering, 932 (1), art. no. 012060, DOI: 10.1088/1757-899X/932/1/012060 | en_US |
dc.identifier.uri | http://hdl.handle.net/123456789/25077 | - |
dc.description | This article is index by Scopus | en_US |
dc.description.abstract | Laser micromachining provide significant effect in thin film solar industrial field especially in determining cell efficiency of each panels. However, there is an issue in determining scribing failure or defect on solar module. This research aims to investigate the defects of laser micromachining process in thin film solar module in manufacturing fields. Machine vision inspection system is used as inspection tools and to investigate the defect of laser micromachining in thin film solar cells. As a result, two major defects is define which is scribe line quality and scribe line position defects in every scribe line. By identifying the defect cause by laser micromachining through machine vision, quality control plan can be taken together to prevent reoccurrence. | en_US |
dc.publisher | IOP Conference Series: Materials Science and Engineering | en_US |
dc.title | Investigation of Scribing Quality Defect of Thin Film Solar Cell Using Machine Vision | en_US |
dc.conference.year | 2020 | en_US |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
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Investigation of Scribing Quality Defect of Thin Film Solar Cell Using Machine Vision.pdf | 31.16 kB | Adobe PDF | View/Open Request a copy |
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