首页|Researchers Submit Patent Application, 'System And Method ForMeasuring Hardness Of Molded Product', for Approval (USPTO20240328917)

Researchers Submit Patent Application, 'System And Method ForMeasuring Hardness Of Molded Product', for Approval (USPTO20240328917)

扫码查看
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – From Washington, D.C., NewsRx journali sts report that a patent application by theinventor SUZUKI, Hiroshi (Kyoto-shi, JP), filed on March 11, 2024, was made available online on October3, 2024.No assignee for this patent application has been made.News editors obtained the following quote from the background information suppli ed by the inventors:“There has been known a rotary compression-molding machine (or a tableting machine: e.g., see JP2020-049516 A or the like) which includes a die table of a turret having die bores, and an upper punchand a lower punch s lidably retained above and below each of the die bores, and which is configured tohorizontally rotate the turret and the punches together and compression-mold a powdery material filledin the die bores when the paired upper and lower punch es pass between an upper roll and a lower rollto obtain a molded product. The m olding machine of this type is preferably adopted for production ofpharmaceutic al tablets, food products, electronic components, and the like.“A production situation needs checking whether there is abnormality by on-demand inspection of propertiesof molded products such as size, weight, composition, and hardness. Quality of the molded productsis typically controlled by sampling a plurality of molded products out of mass-produced molded productsand measuri ng properties of the molded products thus sampled. Target molded products are pi cked upoften with use of a robot arm or the like including a gripper (alternati vely, a hand or a chuck, e.g., seeJP 2019-107739 A or the like).

Emerging TechnologiesMachine LearningPatent ApplicationRobotRobotics

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Oct.18)