Hewlett-Packard Development Company, L.p.

Peridot Print LLC

Victor Diego Gutierrez

Manuel Freire Garcia

Enrique Gurdiel Gonzalez

Jan Morovic

Peter Morovic

Javier Maestro Garcia

Jordi Sanroma Garrit

Sergio Gonzalez Martin

Alex Campa Coloma

Pere Gasparin Talarn

In an example, a method includes acquiring, by a processor and for a set of locations in a fabrication chamber for additive manufacturing, data identifying a first subset of locations associated with a first level of variability in deformations in object generation and a second subset of locations associated with a second, greater, level of variability in deformations object generation. A geometrical compensation model may be derived to compensate for anticipated deformations in object generation by a first additive manufacturing apparatus. The geometrical compensation model may comprise geometrical transformations to apply to object model data representing at least a portion of an object, wherein each geometrical transformation is associated with a location of the set of locations. The first subset of locations may be associated with geometrical transformations determined based objects generated by a plurality of additive manufacturing apparatus and the second subset of locations may be associated with geometrical transformations determined based on objects generated by the first additive manufacturing apparatus.

Geometrical compensation models

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.

Three-dimensional printing with dimensional modification compensation

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.

Dimensional compensations in additive manufacturing

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.

Dimensions in additive manufacturing

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.

Geometrical compensations for additive manufacturing

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.

Predicted object attributes

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.

Dimensional compensations for additive manufacturing

Certain examples described herein relate to generating a Neugebauer Primary area coverage (NPac) vector. In certain cases, an operating state of a printing system is determined. A first NPac vector is obtained, having an initial set of Neugebauer Primaries (NPs). The initial set of NPs comprise a NP that is not implementable with the operating state. A target set of NPs is determined on the basis of the operating state, the target set of NPs being implementable with the operating state. A second NPac vector is generated, the second NPac vector having the target set of NPs.

Generating an area coverage vector

Certain examples described herein relate to printer calibration. In some cases, adjustment data is received, indicating an adjustment to be applied to a given colorant. A Neugebauer Primary area coverage (NPac) vector defining an operating set of Neugebauer Primaries (NPs) is obtained. Configuration data is determined, dependent on the operating set of NPs. The configuration data maps colorant adjustments to relationships between NPs in the operating set, for both an increase and a decrease in the given colorant. In some cases, the configuration data and the adjustment parameters are used to identify first and second subsets of the operating set of NPs. The NPac vector is adjusted by decreasing an area coverage of an NP in the first subset and complementarily increasing an area coverage of an NP in the second subset.

Printer calibration

Certain examples described herein relate to updating a lookup table for an imaging system. An initial lookup table for an imaging system is obtained, the initial lookup table mapping between a first color space and a second color space. A smoothed version of the initial lookup table is also obtained. Further obtained are color property values corresponding to nodes of the lookup tables that map from a vertex-to-vertex axis of the first color space. The color property values are derived from measurements of test areas rendered by the imaging system. For a target node of the smoothed version of the initial lookup table that maps from the vertex-to-vertex axis, a pair of nodes in the initial lookup table are selected based on the obtained color property values. A mapped value in the second color space for the target node is updated, based on an interpolation of mapped values for the pair of nodes in the initial lookup table. The mapped value for the target node is constrained based on a color property value for the target node.

Updating a lookup table for an imaging system

In an example a method includes deriving a print agent coverage vector specifying an area coverage for each of a plurality of elements, wherein each element is associated with a print agent, a print agent combination or an absence of print agent. Deriving the print agent coverage vector comprises, for a first element of the print agent coverage vector, applying a first weighting function which varies based on an intended area color value.

Weighting functions which vary with intended area color values

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.

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Sant Cugat del Valles, Spain

Victor Diego Gutierrez