General Electric Company

Yibo Gao

Yong Yang

Yong Liang Liu

William Thomas Carter

Bin Wei

Andrew Lee Trimmer

Prabhjot Singh

Hong Qing Zhou

Yanzhe Yang

Pinghai Yang

Liming Zhang

Ming Jia

Yingna Wu

Jianping Wu

Meisam Salahshoor Pirsoltan

Huiyu Xu

A system is configured for machining a workpiece (), the workpiece includes an interior surface () that defines an internal passage (). The system includes an electrode () located within the internal passage and electrically isolated from the workpiece, an electrolyte supply, a power supply, and a remover. The electrolyte supply is configured for circulating an electrolyte in a gap between the electrode and the workpiece. The power supply is configured for applying a voltage between the electrode and the workpiece to facilitate smoothing the interior surface. The remover is configured for completely removing the electrode from within the internal passage after smoothing the interior surface.

System and method for machining workpiece and article machined therefrom

A method for removing oxide materials from a crack of a metallic workpiece comprises: infiltrating an alkali solution into the crack in a pressurized atmosphere or an ultrasonic environment; applying an energy to the crack to react the oxide materials with the alkali solution and form a resultant material; and rinsing the resultant material with an acid solution to remove the resultant material from the crack. The method is easier to penetrate into the inside of the cracks, in particular suitable for cleaning narrow and deep cracks.

Method for removing oxide materials from a crack

A process plan optimization method for manufacturing a workpiece by adding a material in a plurality of layers is provided. The method includes: building a predicting model, the predicting model configured to predict a temperature variation of at least a portion of the workpiece; predicting an expected temperature variation of the portion of the workpiece to be manufactured during a given time period based on the predicting model and the process plan; and adjusting the process plan in response to the expected temperature variation of the portion failing to meet a preset condition, to make the expected temperature variation of the portion meet the preset condition.

Additive manufacturing process plan optimization based on predicted temperature variation

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Yibo Gao