72 January/February 2024 | E-Mobility Engineering ensures that corrective actions are targeted and effective.” More than just the number of defects, battery manufacturers need to know what kinds of defects they are and their root causes, another expert notes. “This is the key information you are looking for from the vision system, and we categorise them using AI. Once you know the root cause of a defect such as a pinhole or a scratch, engineers can find a solution to fix it. Unfortunately, manufacturers don’t want to disclose the detail because this is their IP.” Feedback from inspection systems provides insights into manufacturing processes at scale, our visual inspection expert says. Automated scan upload and feature extraction allow for rapid collection and interpretation of data. Automated defect detection ensures that process problems are promptly identified, while automated alerts warn of deviations from quality standards, cueing immediate corrective actions, he explains. He adds that his company’s systems enable download of cell scans and metrology with a click, so that data is readily available for analysis and decision-making in support of problemsolving. “Information generated during inspection is stored at scale for extended periods, preserving the history of each cell. This allows for post-hoc metrology analysis, enabling detailed examinations of past production cycles and facilitating comparisons between gigafactories, cell designs, production time periods, and shifts,” he says. “The data supports r&d efforts by providing information for continuous improvement and innovation. It is also instrumental in upholding product safety standards, identifying potential risks, and proactively addressing safety concerns.” Inspection advances As a totem of progress in inspection technology, the most important thing for customers is detectability – how to detect a defect, another expert explains. “That is not just the camera, the customer solution also depends on the system design including the light source and the lens. “Detectability is a big issue in many industries, and in future with cameras and other sensors we want to improve signal-to-noise ratio because that is the most important element of detecting a defect,” he says.” Another area for improvement is exploiting light beyond the visible, he adds, emphasising the need to move to both UV and IR, including IR wavebands beyond the thermal. Traditionally, many cell manufacturers relied on 2D X-ray methods for inline inspection, but the shift to 3D inline CT systems provides a more comprehensive view of battery components, enabling more accurate, reliable and repeatable measurements and consequent identification of defects and reducing the likelihood of false positives. Preloaded and customised job routines, automation, and AI powered data analysis make CT inspection systems easier to use and yield results more quickly, while CT technology itself is continuously advancing. As parts have grown larger and more complex, more powerful systems have become available. Additionally, new and faster techniques for scanning have been developed. Arguably, the largest push in the field has been integrating advanced AI into reconstruction and image analysis. The principal way in which AI is now making its way into the heart of inspection is through automatic defect recognition (ADR), enabling manufacturers to automate defect analysis workflows. For example, a new system from a leading provider offers AI-based, on-premises ADR software with teachable algorithms that evaluate the quality of a wide range of parts and exploit automated detection of microstructural defects in CT images. “This software provides specific feature analysis with ADR for pass/ fail decisions and fully automated CT workflows. And we are planning to expand the range of this offering,” this company’s expert says. One important thread of development in processing X-ray images involves dealing with the effects of scatter. X-ray scatter artefacts are unwanted signals or disturbances that can appear in an X-ray image due to the scattering of X-ray photons as they interact with the object being imaged. Essentially, photons can change direction after interacting with the atoms in the material, deviating from the primary path intended for imaging, degrading the image by creating background noise or reducing contrast. Our multi-technology inspection system provider offers a hardwareand-software-based system to control scatter that dramatically improves Cylindrical li-ion cell structure revealed by the ZEISS Xradia CrystalCT crystallographic imaging system, which can perform non-destructive mapping of grain morphology in 3D (Image courtesy of ZEISS)
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