Abstract: In an example, a tangible machine-readable medium stores instructions which, when executed by a processor, cause the processor to evaluate a plurality of possible object generation arrangements based on a default separation distance and an enhanced separation distance, wherein the enhanced separation distance is used to assess predefined object sub-portions.

Abstract: In an example, a method includes receiving, at at least one processor, object model data representing at least a portion of an object that is to be generated by an additive manufacturing apparatus by fusing build material within a fabrication chamber. At least one of a plurality of different geometrical compensation models to be applied to the object model data may be selected wherein the geometrical compensation models are to determine geometrical compensations to compensate for object deformation in additive manufacturing. An object generation operation based on a modification of the object model data using the or each selected geometrical compensation mode may be simulated and predicted attributes of the object when generated based on the or each simulation may be displayed. FIG.

Abstract: In an example, a method includes receiving object model data representing at least a portion of an object that is to be generated by an additive manufacturing apparatus by fusing build material within a fabrication chamber. At least one of a number of different geometrical compensation models to be applied to the object model data may be selected, where the geometrical compensation models are to determine geometrical compensations to compensate for object deformation in additive manufacturing. An object generation operation based on a modification of the object model data using the or each selected geometrical compensation mode may be simulated and predicted attributes of the object when generated based on the or each simulation may be displayed.

Abstract: In an example, a method includes receiving, at least one processor, object model data representing at least a portion of an object that is to be generated by an additive manufacturing apparatus by fusing build material within a fabrication chamber. An intended object placement location within the fabrication chamber may be determined, and a dimensional compensation to apply to the object model data may be determined using a mapping resource relating dimensional compensations to object placement locations. The determined dimensional compensation may be applied to the object model data to generate modified object model data using at least one processor.

Abstract: In an example, a method includes receiving, at a processor, an object model describing a geometry of a three-dimensional object, and determining a transformed data model describing a volume containing a modified version of the three-dimensional object as a plurality of categorised contiguous, non-overlapping sub-volumes, wherein the modified version of the three-dimensional object includes a surface offset. Determining the transformed data model may comprises categorising the sub-volumes by defining a first region by determining an area swept by an offset operator when the offset operator is swept around a boundary of the sub-volume and defining a second region, interior to the first region, and indicative of the closest approach of the offset operator to the sub-volume when the offset operator is swept around the boundary. Intersections between a surface of the object model and at least one of the first and second region may be determined.

Abstract: In an example, a method includes receiving, by at least one processor, object model data representing at least a portion of a first object that is to be generated by an additive manufacturing apparatus. An indication of a proportion of the first object which is solid may be determined, and, based thereon, a dimensional compensation value may be determined. The determined dimensional compensation value may be applied to the object model data to determine modified object model data.

Abstract: An example method includes acquiring, by at least one processor, (i) an indication of measured dimensions of objects generated in a common additive manufacturing build operation, wherein the objects include at least one instance of a first object generated based on first object model data and at least one instance of a second object based on second object model data; and (ii) an indication of the orientation of the measured dimensions. Vector components for each of the measured dimensions may be determined based on the indication of the orientation. A first geometrical compensation for use in modifying the first object model data may be determined based on the measured dimensions and the vector components relating to the first object and a second geometrical compensation for use in modifying the second object model data may be determined based on the measured dimensions and the vector components relating to the second object.

Abstract: In an example, a method includes obtaining an indication of a deviation from an expected dimension of at least one dimension of an object generated using an additive manufacturing apparatus. A geometrical compensation model to apply to object model data for generating objects using additive manufacturing to compensate for anticipated deviations in dimensions may be determined from the obtained indication. The geometrical compensation model may comprise a first value to apply to object model data to modify a specification of an external dimension; and a second, different, value to apply to object model data to modify a specification of an internal dimension.

Abstract: An example method includes obtaining, by at least one processor, a plurality of categorised indications of deviations from expected dimensions for at least one object generated using an additive manufacturing apparatus wherein the categories comprise at least two of a first dimension type comprising dimensions which are expected to increase on application of a positive offset to object model data used to generate an object, a second dimension type comprising dimensions which are expected to decrease on application of a positive offset to the object to object model data used to generate an object, and a third dimension type comprising dimensions which are expected to be unaffected by application of an offset to object model data used to generate an object. The method may include determining a geometrical compensation model to apply to object model data for generating objects using additive manufacturing to compensate for anticipated deviations in dimensions.

Abstract: In an example, a machine-readable medium stores instructions which, when executed by a processor, cause the processor to: update a 3D printing geometrical compensation model with at least one correction determined using a combination of a dimensional correction determined from measurements of objects generated using a first geometrical compensation and a dimensional correction determined from measurements of objects generated using a modified version of the first geometrical compensation.

Abstract: In an example, a method may include obtaining a first measurement of a first object generated using additive manufacturing apparatus based on object model data and obtaining a second measurement of a second object generated using the additive manufacturing apparatus based on object model data to which a first geometrical compensation parameter has been applied. An effect of the first geometrical compensation parameter may be determined based on the first and second measurements and, based on the determined effect, the first geometrical compensation parameter may be evaluated.

Abstract: In an example, a machine-readable medium stores instructions which, when executed by a processor may cause the processor to modify data for characterising geometrical modifications for use by each of a plurality of additive manufacturing apparatus, wherein a modification for a particular additive manufacturing apparatus is based on dimensions of objects generated by that apparatus.

Abstract: In an example, a method includes generating a training dataset for an inference model to generate dimensional modifications to apply to object models to compensate for departures from model dimensions in objects generated using additive manufacturing based on those object models. Generating the training dataset may include acquiring, for each of a plurality of generated objects, (i) an indication of a first dimensional inaccuracy and a second dimensional inaccuracy, wherein the first and second dimensional inaccuracies are acquired in a direction of a first axis and relate to respective first and second object dimensions; and (ii) an indication of object placement within a fabrication chamber during object generation.

Abstract: In an example, a method includes receiving, at least one processor, object model data representing at least a portion of an object that is to be generated by an additive manufacturing apparatus by fusing build material within a fabrication chamber, wherein the object model data comprises a mesh model comprising data describing a surface of the object. A geometrical compensation vector may be determined for the object model data, the geometrical compensation vector having a first component applying to a first axis of the fabrication chamber and a second component applying to a second axis of the fabrication chamber. A geometrical compensation to apply to at least one location on the surface of the object may be determined by determining a product of the geometrical compensation vector and a vector indicative of the normal of the object surface at the location and the determined geometrical compensation may be applied to the object model data to generate modified object model data.

Abstract: Example implementations relate to compensating for shrinkage in 3D printing. One example implementation receives an object model to print a corresponding object in a three-dimensional (3D) printer, the object model having a plurality of surface coordinates. A plurality of dimensional modification compensation factors are determined dependent on respective locations within a printing volume of the 3D printer. The object model is adjusted at the plurality of surface coordinates using respective dimensional modification compensation factors depending on the location of the surface coordinates within the printing volume in order to generate a printable object model.

Abstract: In an example, a tangible machine-readable medium stores instructions which, when executed by a processor, cause the processor to evaluate a plurality of possible object generation arrangements based on a default separation distance and an enhanced separation distance, wherein the enhanced separation distance is used to assess predefined object sub-portions.

Abstract: In an example, a method includes generating a training dataset for an inference model to generate dimensional modifications to apply to object models to compensate for departures from model dimensions in objects generated using additive manufacturing based on those object models. Generating the training dataset may include acquiring, for each of a plurality of generated objects, (i) an indication of a first dimensional inaccuracy and a second dimensional inaccuracy, wherein the first and second dimensional inaccuracies are acquired in a direction of a first axis and relate to respective first and second object dimensions; and (ii) an indication of object placement within a fabrication chamber during object generation.

Abstract: In an example, a method includes receiving, at least one processor, object model data representing at least a portion of an object that is to be generated by an additive manufacturing apparatus by fusing build material within a fabrication chamber. An intended object placement location within the fabrication chamber may be determined, and a dimensional compensation to apply to the object model data may be determined using a mapping resource relating dimensional compensations to object placement locations. The determined dimensional compensation may be applied to the object model data to generate modified object model data using at least one processor.

Abstract: In an example, a method includes receiving, at at least one processor, object model data representing at least a portion of an object that is to be generated by an additive manufacturing apparatus by fusing build material within a fabrication chamber. At least one of a plurality of different geometrical compensation models to be applied to the object model data may be selected wherein the geometrical compensation models are to determine geometrical compensations to compensate for object deformation In additive manufacturing. An object generation operation based on a modification of the object model data using the or each selected geometrical compensation mode may be simulated and predicted attributes of the object when generated based on the or each simulation may be displayed.

Abstract: In an example, a method includes receiving, at at least one processor, object model data representing at least a portion of an object that is to be generated by an additive manufacturing apparatus by fusing build material within a fabrication chamber. An intended object placement location within the fabrication chamber may be determined, and a dimensional compensation to apply to the object model data may be determined using a mapping resource relating dimensional compensations to object placement locations. The determined dimensional compensation may be applied to the object model data to generate modified object model data using at least one processor.