EuroWire November 2020

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bed 3D printers to assess the quality of printed parts in real time. The Peregrine system is said to support the advanced manufacturing “digital thread” being developed at ORNL that collects and analyses data through every step of the manufacturing process, from design to feedstock selection, to print build and material testing. “Capturing that information creates a digital clone for each part, providing a trove of data from the rawmaterial to the operational component,” said Vincent Paquit, who is leading advanced manufacturing data analytics research as part of ORNL’s imaging, signals and machine learning group. “We then use that data to qualify the part and to inform future builds across multiple part geometries and with multiple materials, achieving new levels of automation andmanufacturing quality assurance.” The digital thread supports the anticipated factory of the future, where custom parts are conceived using CAD and then produced by self-correcting 3D printers via a communications network, all at a lower cost in terms of time, energy and materials. According to ORNL, the concept requires a process control method that ensures every part produced by the printers is ready for immediate use and installation. Peregrine is being developed for powder bed printers because, while popular for the production of metal parts, they are vulnerable to problems – such as uneven distribution of the

for early somatosensory information processing; and a “parse neural network”to fuse the visual and somatosensory information together. The result is a system thought to recognise human gestures more accurately and efficiently than any existing method. To capture reliable sensory data from hand gestures, the research team fabricated a transparent, stretchable strain sensor that adheres to the skin but cannot be seen in camera images. Lead author Professor Chen Xiaodong, from the School of Materials Science and Engineering at NTU, said, “Our data fusion architecture has its own unique bio-inspired features which include a man-made system resembling the somatosensory- visual fusion hierarchy in the brain. We believe such features make our architecture unique to existing approaches. “Compared to rigid wearable sensors that do not form an intimate enough contact with the user for accurate data collection, our innovation uses stretchable strain sensors [and] comfortably attaches onto the human skin. This allows for high quality signal acquisition, which is vital to high precision recognition tasks.” The NTU research team is now looking to build a VR and AR system based on the AI system for use in areas such as home- based rehabilitation and entertainment technologies.

Peregrine spots the flaws in 3D printing Researchers at Tennessee’s Oak Ridge National Laboratory (ORNL) have developed Peregrine, an AI software package for powder

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November 2020