South Korea’s LG Energy Solution Ltd. is speeding up digitalization and automation in its battery plants across the world with smart solutions in partnership with a leading domestic industrial solution research institute that boasts of Lidar-aided 3D modeling technology and other smart factory solutions.

The company said Wednesday that it signed a memorandum of understanding (MOU) with the Research Institute of Industrial Science & Technology (RIST) on Tuesday to collaborate on smart manufacturing technologies, mainly focusing on digital twin technology. RSIT, established by Korean steelmaking giant POSCO in 1987, is a renowned local technology research institute for lithium-ion batteries, renewable energy, and smart grids.

Based on their partnership, the two parties will research smart factory solutions, especially the digital twin technology. A digital twin is a computer program that uses real-world data to create real-world like simulations that can predict how a product or process will perform. The program integrates the internet of things, artificial intelligence, and software analytics technologies to enhance output and reduce operational errors. LG Energy Solution will become the first company to adopt RSIT’s light detection and ranging (LiDAR) technology for 3-D laser scanning or modeling for facility designing.

Both sides also agreed on joint research on remote monitoring and bilateral support for human resources and technologies.

LG Energy Solution, eager to build intelligent manufacturing systems, signed a deal with Siemens last year to work together to turn its battery plants into smart factories. It has adopted the German industrial solutions provider’s software and other technologies to build an intelligent manufacturing system. It also made a factory monitoring control center (FMCC) to detect errors in operating processes.

Last February, the company hired Pyun Kyung-sup, a former data scientist from Nvidia, as its chief digital officer to speed up its effort to upgrade battery quality through intelligent manufacturing.

By Jenny Lee

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