TY - GEN
T1 - Photoluminescence Imaging for Industrial Quality Control during Manufacturing of Thin-Film Solar Cells
AU - Zikulnig, Johanna
AU - Mühleisen, Wolfgang
AU - Simor, Marcel
AU - Gevaerts, Veronique
AU - De Biasio, Martin
PY - 2022/12/8
Y1 - 2022/12/8
N2 - Thin- film photovoltaics (PV), and in particular Copper Indium Gallium Selenide (CIGS) technologies, will play an important role in the turnaround in inevitable energy policy due to their high efficiencies, easy installation, high product flexibility, and a lower carbon footprint when compared to silicon solar cells. However, due to the delicate processing and associated costs in the manufacturing of CIGS cells, inline quality control during production is a hot topic for PV industry. In this work we demonstrate that photoluminescence (PL) imaging can be a powerful enabling technology for improving the process efficiency. Using Python based image processing and analysis, defects that lead to failure of individual cells can be detected early in the production process, which ultimately saves resources and costs by not further processing nonconformal batches.
AB - Thin- film photovoltaics (PV), and in particular Copper Indium Gallium Selenide (CIGS) technologies, will play an important role in the turnaround in inevitable energy policy due to their high efficiencies, easy installation, high product flexibility, and a lower carbon footprint when compared to silicon solar cells. However, due to the delicate processing and associated costs in the manufacturing of CIGS cells, inline quality control during production is a hot topic for PV industry. In this work we demonstrate that photoluminescence (PL) imaging can be a powerful enabling technology for improving the process efficiency. Using Python based image processing and analysis, defects that lead to failure of individual cells can be detected early in the production process, which ultimately saves resources and costs by not further processing nonconformal batches.
U2 - 10.1109/SENSORS52175.2022.9967278
DO - 10.1109/SENSORS52175.2022.9967278
M3 - Conference Paper
BT - IEEE Sensors Conference 2022
CY - 2022 IEEE Sensors
ER -