Abstract
The demand for flexible large area optoelectronic devices such as organic light-emitting diodes (OLEDs) and organic photovoltaics (OPVs) is growing. Roll-to-roll (R2R) printing enables cost-efficient industrial production of optoelectronic devices. The performance of electronic devices may significantly suffer from local electrical defects. The dark lock-in infrared thermography (DLIT) method is an effective non-destructive testing (NDT) tool to identify such defects as hot spots. In this study, a DLIT inspection system was applied to visualize the defects of R2R printed silver conductors on flexible plastic substrates. A two-stage automated defect recognition (ADR) methodology was proposed to detect and localize two types of typical electrical defects, which are caused by complete or partial breaks on the printed conductive wires, based on localized segmentation and thresholding methods.
Highlights
The high-volume production of flexible electronics using roll-to-roll (R2R) manufacturing technologies is a promising upscaling solution for the organic electronics industry [1,2,3,4]
The thermal image post-processing procedure involves two main stages: Stage 1: Each individual silver printed conductive wire was identified by using image segmentation. This was compared with the designed printing patterns which enabled the completely broken wires to be automatically detected; Stage 2: Within the identified printed conductors, the local electrical defects on the thin film, which are shown as hot spots in the thermal images, were automatically detected using the thresholding method
dark lock-in infrared thermography (DLIT) Trials DLIT tests were carried out on the R2R printed thin film samples provided by VTT
Summary
The high-volume production of flexible electronics using roll-to-roll (R2R) manufacturing technologies is a promising upscaling solution for the organic electronics industry [1,2,3,4]. Imaging are able to reveal the details on registration, defects, particles, shunts and processing variations affecting electrical functionality [12,13,14,15] These techniques have proven useful for inline inspection, monitoring and process control [12,16,17,18,19]. The thermal image post-processing procedure involves two main stages: Stage 1: Each individual silver printed conductive wire was identified by using image segmentation This was compared with the designed printing patterns which enabled the completely broken wires to be automatically detected; Stage 2: Within the identified printed conductors, the local electrical defects on the thin film, which are shown as hot spots in the thermal images, were automatically detected using the thresholding method.
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