This case study focuses on KCARBON, the Korea Carbon Industry Promotion Agency, which develops advanced carbon fiber manufacturing technologies. KCARBON sought to create a new additive formulation that coats carbon fibers during production to enhance the physical and mechanical properties of the final fiber and composite. In addition to meeting multiple high‑priority performance criteria, the organization wanted to evaluate machine learning‑guided product development against traditional R&D approaches. By applying AI‑driven development, KCARBON accelerated formulation discovery, explored innovative design paths, and demonstrated how data‑driven methods can improve efficiency, performance, and decision‑making in advanced materials manufacturing.

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