A computerised data handling procedure for defect detection and analysis for large area substrates manufactured by roll-to-roll process

H. Muhamedsalih, Mohamed Elrawemi, L. Blunt, Xiangqi Lan, H. Martin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The development of optical on-line/in-process surface inspection and characterisation systems for flexible roll to roll (R2R) thin film barriers used for photo-voltaic (PV) modules is a core research goal for the EU funded NanoMend project. Micro and nano scale defects in the ALD (atomic layer deposition) Al2O3 barrier coating produced by R2R techniques can affect the PV module efficiency and lifespan. The presence of defects has been shown to have a clear correlation with the water-vapour-transmission-rate (WVTR). Hence, in order to improve the PV cell performance and lifespan the barrier film layer must prevent water vapour ingress. One of the main challenges for the application of in process metrology is how to assess large and multiple measurement data sets obtained from an in process optical instrument. Measuring the surface topography over large area substrates (approximately 500 mm substrate width) with a limited field-of-view (FOV) of the optical instrument will produce hundreds/thousands of measurement files. Assessing each file individually to find and analyse defects manually is time consuming and impractical. This paper reports the basis of a computerised solution to assess these files by monitoring and extracting areal surface topography parameters. Comparing parameter values to an experimentally determined threshold value, obtained from extensive lab-based measurement of Al2O3 ALD coated films, can indicate the existence of the defects within a given FOV. This process can be repeated automatically for chosen parameters and the existence of defects can be indicated for the entire set of measurement files spontaneously without interaction from the inspector. A running defect log and defect statistics associated with the captured set of data files can be generated. This paper outlines the implementation of the auto-defect logging using advanced areal parameters, and its application in a proof of concept system at the Centre for Process Innovation (UK) is discussed.

LanguageEnglish
Title of host publicationLaser Metrology and Machine Performance XI - 11th International Conference and Exhibition on Laser Metrology, Machine Tool, CMM and Robotic Performance, LAMDAMAP 2015
Publishereuspen
Pages82-89
Number of pages8
ISBN (Electronic)9780956679055
Publication statusPublished - 2015
Event11th International Conference and Exhibition on Laser Metrology, Coordinate Measuring Machine and Machine Tool Performance - , United Kingdom
Duration: 17 Mar 201518 Mar 2015
Conference number: 11

Conference

Conference11th International Conference and Exhibition on Laser Metrology, Coordinate Measuring Machine and Machine Tool Performance
Abbreviated titleLAMDAMAP 2015
CountryUnited Kingdom
Period17/03/1518/03/15

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files
defects
atomic layer epitaxy
field of view
water vapor
topography
modules
photovoltaic cells
metrology
inspection
statistics
coatings
thresholds
thin films
interactions

Cite this

Muhamedsalih, H., Elrawemi, M., Blunt, L., Lan, X., & Martin, H. (2015). A computerised data handling procedure for defect detection and analysis for large area substrates manufactured by roll-to-roll process. In Laser Metrology and Machine Performance XI - 11th International Conference and Exhibition on Laser Metrology, Machine Tool, CMM and Robotic Performance, LAMDAMAP 2015 (pp. 82-89). euspen.
Muhamedsalih, H. ; Elrawemi, Mohamed ; Blunt, L. ; Lan, Xiangqi ; Martin, H. / A computerised data handling procedure for defect detection and analysis for large area substrates manufactured by roll-to-roll process. Laser Metrology and Machine Performance XI - 11th International Conference and Exhibition on Laser Metrology, Machine Tool, CMM and Robotic Performance, LAMDAMAP 2015. euspen, 2015. pp. 82-89
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abstract = "The development of optical on-line/in-process surface inspection and characterisation systems for flexible roll to roll (R2R) thin film barriers used for photo-voltaic (PV) modules is a core research goal for the EU funded NanoMend project. Micro and nano scale defects in the ALD (atomic layer deposition) Al2O3 barrier coating produced by R2R techniques can affect the PV module efficiency and lifespan. The presence of defects has been shown to have a clear correlation with the water-vapour-transmission-rate (WVTR). Hence, in order to improve the PV cell performance and lifespan the barrier film layer must prevent water vapour ingress. One of the main challenges for the application of in process metrology is how to assess large and multiple measurement data sets obtained from an in process optical instrument. Measuring the surface topography over large area substrates (approximately 500 mm substrate width) with a limited field-of-view (FOV) of the optical instrument will produce hundreds/thousands of measurement files. Assessing each file individually to find and analyse defects manually is time consuming and impractical. This paper reports the basis of a computerised solution to assess these files by monitoring and extracting areal surface topography parameters. Comparing parameter values to an experimentally determined threshold value, obtained from extensive lab-based measurement of Al2O3 ALD coated films, can indicate the existence of the defects within a given FOV. This process can be repeated automatically for chosen parameters and the existence of defects can be indicated for the entire set of measurement files spontaneously without interaction from the inspector. A running defect log and defect statistics associated with the captured set of data files can be generated. This paper outlines the implementation of the auto-defect logging using advanced areal parameters, and its application in a proof of concept system at the Centre for Process Innovation (UK) is discussed.",
author = "H. Muhamedsalih and Mohamed Elrawemi and L. Blunt and Xiangqi Lan and H. Martin",
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Muhamedsalih, H, Elrawemi, M, Blunt, L, Lan, X & Martin, H 2015, A computerised data handling procedure for defect detection and analysis for large area substrates manufactured by roll-to-roll process. in Laser Metrology and Machine Performance XI - 11th International Conference and Exhibition on Laser Metrology, Machine Tool, CMM and Robotic Performance, LAMDAMAP 2015. euspen, pp. 82-89, 11th International Conference and Exhibition on Laser Metrology, Coordinate Measuring Machine and Machine Tool Performance, United Kingdom, 17/03/15.

A computerised data handling procedure for defect detection and analysis for large area substrates manufactured by roll-to-roll process. / Muhamedsalih, H.; Elrawemi, Mohamed; Blunt, L.; Lan, Xiangqi; Martin, H.

Laser Metrology and Machine Performance XI - 11th International Conference and Exhibition on Laser Metrology, Machine Tool, CMM and Robotic Performance, LAMDAMAP 2015. euspen, 2015. p. 82-89.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - A computerised data handling procedure for defect detection and analysis for large area substrates manufactured by roll-to-roll process

AU - Muhamedsalih, H.

AU - Elrawemi, Mohamed

AU - Blunt, L.

AU - Lan, Xiangqi

AU - Martin, H.

PY - 2015

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N2 - The development of optical on-line/in-process surface inspection and characterisation systems for flexible roll to roll (R2R) thin film barriers used for photo-voltaic (PV) modules is a core research goal for the EU funded NanoMend project. Micro and nano scale defects in the ALD (atomic layer deposition) Al2O3 barrier coating produced by R2R techniques can affect the PV module efficiency and lifespan. The presence of defects has been shown to have a clear correlation with the water-vapour-transmission-rate (WVTR). Hence, in order to improve the PV cell performance and lifespan the barrier film layer must prevent water vapour ingress. One of the main challenges for the application of in process metrology is how to assess large and multiple measurement data sets obtained from an in process optical instrument. Measuring the surface topography over large area substrates (approximately 500 mm substrate width) with a limited field-of-view (FOV) of the optical instrument will produce hundreds/thousands of measurement files. Assessing each file individually to find and analyse defects manually is time consuming and impractical. This paper reports the basis of a computerised solution to assess these files by monitoring and extracting areal surface topography parameters. Comparing parameter values to an experimentally determined threshold value, obtained from extensive lab-based measurement of Al2O3 ALD coated films, can indicate the existence of the defects within a given FOV. This process can be repeated automatically for chosen parameters and the existence of defects can be indicated for the entire set of measurement files spontaneously without interaction from the inspector. A running defect log and defect statistics associated with the captured set of data files can be generated. This paper outlines the implementation of the auto-defect logging using advanced areal parameters, and its application in a proof of concept system at the Centre for Process Innovation (UK) is discussed.

AB - The development of optical on-line/in-process surface inspection and characterisation systems for flexible roll to roll (R2R) thin film barriers used for photo-voltaic (PV) modules is a core research goal for the EU funded NanoMend project. Micro and nano scale defects in the ALD (atomic layer deposition) Al2O3 barrier coating produced by R2R techniques can affect the PV module efficiency and lifespan. The presence of defects has been shown to have a clear correlation with the water-vapour-transmission-rate (WVTR). Hence, in order to improve the PV cell performance and lifespan the barrier film layer must prevent water vapour ingress. One of the main challenges for the application of in process metrology is how to assess large and multiple measurement data sets obtained from an in process optical instrument. Measuring the surface topography over large area substrates (approximately 500 mm substrate width) with a limited field-of-view (FOV) of the optical instrument will produce hundreds/thousands of measurement files. Assessing each file individually to find and analyse defects manually is time consuming and impractical. This paper reports the basis of a computerised solution to assess these files by monitoring and extracting areal surface topography parameters. Comparing parameter values to an experimentally determined threshold value, obtained from extensive lab-based measurement of Al2O3 ALD coated films, can indicate the existence of the defects within a given FOV. This process can be repeated automatically for chosen parameters and the existence of defects can be indicated for the entire set of measurement files spontaneously without interaction from the inspector. A running defect log and defect statistics associated with the captured set of data files can be generated. This paper outlines the implementation of the auto-defect logging using advanced areal parameters, and its application in a proof of concept system at the Centre for Process Innovation (UK) is discussed.

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M3 - Conference contribution

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BT - Laser Metrology and Machine Performance XI - 11th International Conference and Exhibition on Laser Metrology, Machine Tool, CMM and Robotic Performance, LAMDAMAP 2015

PB - euspen

ER -

Muhamedsalih H, Elrawemi M, Blunt L, Lan X, Martin H. A computerised data handling procedure for defect detection and analysis for large area substrates manufactured by roll-to-roll process. In Laser Metrology and Machine Performance XI - 11th International Conference and Exhibition on Laser Metrology, Machine Tool, CMM and Robotic Performance, LAMDAMAP 2015. euspen. 2015. p. 82-89