Abstract: Examples of methods are described herein. In some examples, a method includes determining a quantity of inner voxels in a canonical direction from each surface voxel of a set of surface voxels of a three-dimensional (3D) object model. In some examples, the method includes generating an encoded representation of the 3D object model, the encoded representation indicating a location of each surface voxel and the quantity of inner voxels for each surface voxel.

Abstract: Examples of methods for object manufacturing visualization by an electronic device are described herein. In some examples, a predicted thermal image of additive manufacturing is determined using a machine learning model. In some examples, a captured thermal image is obtained. In some examples, a graphical overlay of the predicted thermal image with the captured thermal image is presented.

Abstract: According to examples, an apparatus may include a processor and a memory on which is stored machine readable instructions that when executed by the processor are to cause the processor to access a reduced resolution three-dimensional (3D) model file of an object to be built in a build bed of a 3D printing system, the reduced resolution 3D model file comprising a reduced resolution file of a first resolution 3D model file of the object. The instructions may also cause the processor to determine a packing arrangement for the object and a plurality of other objects to be built in the build bed through use of the reduced resolution 3D model file and output the determined packing arrangement for the 3D printing system to print the object and the other objects.

Abstract: According to examples, a three-dimensional (3D) fabrication system may include fabrication components and a controller. The controller may control the fabrication components to fabricate parts of a 3D object in a build envelope, the parts to be assembled together to form the object, and in which the parts are fabricated at locations corresponding to relative positions of the parts with respect to each other in the assembled object. The controller may also control the fabrication components to fabricate a cage around the parts in the build envelope.

Abstract: Examples of methods for object manufacturing visualization by an electronic device are described herein. In some examples, a predicted thermal image of additive manufacturing is determined using a machine learning model. In some examples, a captured thermal image is obtained. In some examples, a graphical overlay of the predicted thermal image with the captured thermal image is presented.

Abstract: Examples of methods for fault prediction model training with audio data are described herein. In some examples, service event data and audio data corresponding to client devices are received. In some examples, a portion of the audio data is selected based on the service event data. In some examples, a machine learning model is trained for fault prediction based on the portion of audio data.

Abstract: According to examples, an apparatus may include a processor and a memory on which is stored machine readable instructions that when executed by the processor are to cause the processor to access a reduced resolution three-dimensional (3D) model file of an object to be built in a build bed of a 3D printing system, the reduced resolution 3D model file comprising a reduced resolution file of a first resolution 3D model file of the object. The instructions may also cause the processor to determine a packing arrangement for the object and a plurality of other objects to be built in the build bed through use of the reduced resolution 3D model file and output the determined packing arrangement for the 3D printing system to print the object and the other objects.