Abstract: Examples of methods for object deformation determination are described herein. In some examples, a method includes aligning a first bounding box of a three-dimensional (3D) object model with a second bounding box of a scan. In some examples, the method includes determining a deformation between the 3D object model and the scan based on the alignment.

Abstract: Examples of methods for object packings are described herein. In some examples, a method includes loading a first object in a first subset of a volume. In some examples, the method includes determining, using a genetic procedure, an arrangement of second objects in a second subset of the volume to produce a packing that includes the first object and the second objects.

Abstract: Examples of methods for object packing genetic procedures are described herein. In some examples, a method includes generating chromosomes in a genetic procedure. In some examples, each chromosome indicates a packing of objects in a volume. In some examples, the method includes determining a stagnant generation quantity that indicates an amount of generations subsequent to a leading generation with a leading chromosome score. In some examples, the method includes terminating the genetic procedure based on the stagnant generation quantity.

Abstract: Examples of methods for object packings are described herein. In some examples, a method includes generating chromosomes in a genetic procedure. In some examples, each chromosome indicates a packing of objects in a volume. In some examples, the method also includes determining uniformity scores corresponding to the chromosomes. In some examples, each uniformity score is based on object orientation similarity. In some examples, the method further includes selecting a chromosome based on the uniformity scores.

Abstract: An example non-transitory computer-readable medium includes instructions that, when executed by a processor, cause the processor to retrieve a plurality of parts to be three-dimensionally (3D) printed and an output rate indicative of a rate at which previous 3D printed parts have been output, select a packing parameter that results in a packing time corresponding to the output rate, and compute a part packing of the plurality of parts for a print bed according to the packing parameter.

Abstract: Examples of methods for determining chromosome expiration are described herein. In some examples, a method includes generating, in a genetic procedure, chromosomes indicating object packing positions. In some examples, the method includes determining whether a chromosome of the chromosomes is expired. In some examples, the method includes excluding the chromosome from a subsequent generation in response to determining that the chromosome is expired.

Abstract: Examples of methods for determining object packings are described herein. In some examples, a method includes determining, for each of a plurality of objects, an initial orientation corresponding to a minimum bounding box. In some examples, the method includes determining a packing of the plurality of objects using the initial orientations with a genetic procedure.

Abstract: Examples of methods for point cloud alignment are described herein. In some examples, a method includes orienting a model point cloud or a scanned point cloud based on a set of initial orientations. In some examples, the method includes determining, using a first portion of a machine learning model, first features of the model point cloud and second features of the scanned point cloud. In some examples, the method includes determining, using a second portion of the machine learning model, correspondence scores between the first features and the second features based on the set of initial orientations. In some examples, the method includes globally aligning the model point cloud and the scanned point cloud based on the correspondence scores.

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 determining displacement maps are described herein. In some examples of the methods, a method includes determining a displacement map for a three-dimensional (3D) object model based on a compensated point cloud. In some examples, the method includes assembling the displacement map on the 3D object model for 3D manufacturing.

Abstract: Examples of methods for predicting object deformations are described herein. In some examples, a method includes predicting a point cloud. In some examples, the predicted point cloud indicates a predicted object deformation. In some examples, the point cloud may be predicted using a machine learning model and edges determined from an input point cloud.

Abstract: Examples of methods for model prediction are described herein. In some examples, a method includes predicting a compensated model. In some examples, the compensated model is predicted based on a three-dimensional (3D) object model. In some examples, a method includes predicting a deformed model. In some examples, the deformed mode is predicted based on the compensated model.

Abstract: Examples of methods for object deformation determination are described herein. In some examples, a method includes aligning a first bounding box of a three-dimensional (3D) object model with a second bounding box of a scan. In some examples, the method includes determining a deformation between the 3D object model and the scan based on the alignment.

Abstract: Examples of methods for registering objects are described herein. In some examples, a method includes determining a set of overlap scores based on a set of orientations between a first bounding box of a three-dimensional (3D) object model and a second bounding box of a 3D scan of an object. In some examples, the method includes registering the 3D scan with the 3D object model based on the set of overlap scores.

Abstract: In an example, an apparatus includes an image processing system, a print engine, and a vision system. The image processing system generates electronic signals based on a model of an object to be fabricated using an additive manufacturing process. The print engine performs the additive manufacturing process in a plurality of passes based on the electronic signals. The vision system acquires a plurality of thermal images of the plurality of passes and assigns individual passes to individual images based on data acquired during a build of a calibration object by the additive manufacturing process. The print engine may further include a material coater to spread a powder coating material, a plurality of fluid ejection devices to eject a fusing agent, and an emitter to emit energy to fuse the fusing agent and the powder coating material into a layer of the object to be fabricated.

Abstract: In some examples, with respect to region of interest monitoring and control for additive manufacturing, a blob detection analysis may be performed on first and second component images associated with additive manufacturing of a component, and blobs that remain a same shape and include same centroids on the first and second component images may be identified. A further blob detection analysis may be performed on first and second thermal images associated with the first and second component images, and a determination may be made as to whether one of the identified blobs includes a same shape and a different centroid between the first and second thermal images. Based on a determination that the one of the identified blobs includes the same shape and the different centroid, an indication of a thermal camera misalignment associated with the additive manufacturing may be generated.

Abstract: 3-D printing batch analysis is disclosed. A disclosed example apparatus includes a processor to generate a plurality of batches, wherein each of the batches represent an arrangement of a plurality of parts to be printed in a volume, discretize the batches into slices, and determine risk values of the slices based on the respective geometric primitives. The processor is to also determine aggregate risk values corresponding to the batches based on the risk values of the slices of the respective batches, and select a batch of the plurality of batches based on the aggregate risk values. The example apparatus also includes a printer to print the selected batch in the volume.

Abstract: Systems and methods of predicting temperature during a build of a three-dimensional (3D) part include determining a temperature profile at a plurality of layers of a part based on geometric characteristics of the 3D part as defined by a 3D part file, and adjusting a process parameter of the build based on the determined temperature.

Abstract: In an example of a method for determining a thermal footprint for a three-dimensional (3D) printed part, a part to be printed by a 3D printer is identified. A thermal footprint for the part is determined based on part geometry and heat transfer associated with printing the part.

Abstract: Examples of methods for part packing are described herein. In some examples, a first subset and a second subset of a set of parts are determined. In some examples a first packing of the first subset is determined. In some examples, a second packing of the second subset is determined based on the first packing.