Kobe Steel had 62 patents in future of work during Q1 2024. The patents filed by Kobe Steel Ltd in Q1 2024 focus on innovative systems and methods for welding defect detection, target locus determination for attachments, distance detection for work machines, information acquisition for attachments and cargo, and target path changing systems for attachments. These inventions aim to improve efficiency, accuracy, and safety in various industrial processes. GlobalData’s report on Kobe Steel gives a 360-degree view of the company including its patenting strategy. Buy the report here.
Kobe Steel grant share with future of work as a theme is 33% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Manufacturing-log monitoring device, manufactured-object production system, and manufacturing-log monitoring method (Patent ID: US20240091885A1)
The patent filed by Kobe Steel Ltd. describes a shape sensor for acquiring a shape profile along the extension direction of a weld bead and a control unit that includes a welding information acquisition unit and a defect candidate extraction unit. The welding information acquisition unit gathers data during the formation of an adjacent weld bead, while the defect candidate extraction unit identifies angle characteristic portions in the existing weld bead and associates them with welding characteristic portions to extract defect candidates. The device aims to monitor the additive manufacturing process and estimate defects based on process information.
The claims detail the components and processes involved in the additive-manufacturing process monitoring device, including the acquisition of welding information such as voltage, current, filler material feed rate, and molten pool status. The defect candidate extraction unit calculates the occurrence frequency of defect candidates and estimates defect size in the additively manufactured object. The method and system described in the patent aim to improve the monitoring and detection of defects in additively manufactured objects by analyzing shape profiles, welding information, and defect candidates.
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