Part distortion monitoring in additive manufacturing using machining

• An in-situ method for part distortion detection using machining of additively manufactured parts is described. • A method to synchronously monitor the cutting power and tool position during the machining process is described. • A novel approach to detect tool entry in the workpiece and tool exit using the power standard deviation metric is described. • The method can detect workpiece shape to within 2 mm accuracy using synchronized tool position data with cutting power • The proposed method is low-cost and computationally inexpensive and can be used in a hybrid machine tool to periodically check part distortion in the additive build. In additive manufacturing, accumulation of residual stresses can result in severe part distortion from the desired preform shape. Current methods for in-situ part distortion monitoring in additive manufacturing typically require expensive sensors, or capital equipment, and require time-consuming post-processing to understand the shape deviation. This paper presents an in-situ method, in the context of hybrid manufacturing, for part distortion detection using machining of additively manufactured parts. As a surrogate, three test artifacts were used to represent different distorted geometries. The tool axis positions from the machine tool controller and the cutting power were monitored during a facing operation. Cutting power data was used to detect the tool entry and exit in the workpiece using a novel approach with power standard deviation metric. The workpiece geometry and distorted configuration was subsequently predicted for positional and rotational deviations to within 2 mm accuracy using synchronized tool position data with cutting power. The proposed method can be used in a hybrid (additive and subtractive) machine tool to periodically check part distortion in the additive build. The method is applicable for any additive process and is low-cost and computationally inexpensive.