General Electric Company

Oliver Crispin Robotics Limited

Joanna Mechelle Jayawickrema

Veeraraju Vanapalli

Ruben Egberto Fairman

Johnnattan Tennessee Ugarte

Andrew Jean Desrosiers

Xuefeng Zhang

Jun Zheng Hu

Kishore Vetcha

Ryan Antony Lozier

Andrew Crispin Graham

Ali Can

Thomas Graham Spears

Wayne Ray Grady

Yousef Ahmed Al-Kofahi

Tim Henri Ann Francois

A method for forming a component includes estimating a dosing plan for powder of a powder bed fusion (PBF) system needed to form the component. The dosing plan includes powder dosing requirements needed per layer to form the component. The method includes providing the dosing plan to a controller of the PBF system. Further, the method includes regulating the powder being supplied to a build chamber of the PBF system from a supply chamber of the PBF system based on the dosing plan. In addition, the method includes additively manufacturing the component via the PBF system using the powder.

Systems and methods for estimating powder dosing in additive manufacturing processes

An extension tool has a proximal end and a distal end and comprises a plurality of sequentially arranged links moveable relative to one another and a support member defining the distal end and including a first wheel disposed at the distal end and a second wheel spaced apart from the first wheel. Additionally, or alternatively, an extension tool may comprise a plurality of windows defined in the plurality of sequentially arranged links. The windows are defined periodically along the plurality of sequentially arranged links such that a periodicity of the widows corresponds to a periodicity of a plurality of features of the component.

Extension tool

A system monitoring an additive manufacturing (AM) machine recoat operation includes an automatic defect recognition subsystem having a predictive model catalog each applicable to a product and to one recoat error indication having a domain dependent feature, the predicative models representative of a recoat error indication appearance at a pixel level of an image captured during recoat operations. The system includes an online monitoring subsystem having an image classifier unit that classifies recoat error indications at the pixel level based on predictive models selected on their metadata, a virtual depiction unit that creates a virtual depiction of an ongoing AM build from successive captured image, and a processor unit to monitor the build for recoat error indications, classify a detected indication, and provide a determination regarding the severity of the detected indication on the ongoing build. A method and a non-transitory computer-readable medium are also disclosed.

Recoater automated monitoring systems and methods for additive manufacturing machines

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Mason, OH, United States of America

Joanna Mechelle Jayawickrema