MODIFICATION DATA FOR ADDITIVE MANUFACTURING

• US 20190095555A1
• Filed: 03/18/2016
• Published: 03/28/2019
• Est. Priority Date: 03/18/2016
• Status: Active Grant

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Lopez, Miguel Angel, Sanchez Ribes, Salvador, Garcia, Luis
• Granted Patent: US 11,182,517 B2
• Time in Patent Office: Days
• CPC Class Codes: B22F 10/28 Powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM]
• CPC Class Codes: B22F 10/80 Data acquisition or data processing
• CPC Class Codes: B29C 64/135 the energy source being concentrated, e.g. scanning lasers or focused light sources
• CPC Class Codes: B29C 64/153 using layers of powder being selectively joined, e.g. by selective laser sintering or melting
• CPC Class Codes: B29C 64/165 using a combination of solid and fluid materials, e.g. a powder selectively bound by a liquid binder, catalyst, inhibitor or energy absorber
• CPC Class Codes: B29C 64/386 Data acquisition or data processing for additive manufacturing
• CPC Class Codes: B29C 64/393 for controlling or regulating additive manufacturing processes
• CPC Class Codes: B33Y 50/00 Data acquisition or data processing for additive manufacturing
• CPC Class Codes: B33Y 50/02 for controlling or regulating additive manufacturing processes
• CPC Class Codes: G06F 2113/10 Additive manufacturing, e.g. 3D printing
• CPC Class Codes: G06F 2119/08 Thermal analysis or thermal optimisation
• CPC Class Codes: G06F 2119/18 Manufacturability analysis or optimisation for manufacturability
• CPC Class Codes: G06F 30/00 Computer-aided design [CAD]
• CPC Class Codes: G06F 30/17 Mechanical parametric or variational design
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: Y02P 10/25 Process efficiency
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

In an example, a method includes analysing, using at least one processor, object model data representing at least a portion of an object to be generated by an additive manufacturing apparatus by fusing a build material to determine at least one predicted object generation temperature. The method may further include identifying, using at least one processor and from said analysing, a feature of the at least a portion of the object associated with a predicted object generation temperature which is below a fusing temperature of build material to be used in object generation. The method may further include determining, using at least one processor, modification data to be used in object generation, the modification data being to increase a temperature of the feature in object generation.

Claims

1. A method comprising:

analysing, using at least one processor, object model data representing at least a portion of an object to be generated by an additive manufacturing apparatus by fusing build material to determine at least one predicted object generation temperature;

identifying, using at least one processor and from said analysing, a feature of the at least a portion of the object associated with a predicted object generation temperature which is below a fusing temperature of build material to be used in object generation; and

determining, using at least one processor, modification data to be used in object generation, the modification data being to increase a temperature of the feature in object generation.

2. The method of claim 1 in which analysing the object model data comprises identifying at least one feature of the at least a portion of the object having at least one dimension which is below a threshold size;

and

when a feature having at least one dimension which is below a threshold size is identified, determining at least one predicted object generation temperature for a region of the object including the feature.

3. The method of claim 1 in which analysing the object model data comprises:

determining, for at least a portion of the object, an initial object volume to be occupied by the object or object portion;

reducing the initial object volume by a threshold amount in at least one spatial dimension to provide an eroded object volume;

increasing the eroded object volume in the at least one spatial dimension by the threshold amount to provide a dilated object volume; and

comparing the dilated object volume to the initial object volume.

4. The method of claim 1 in which analysing the object model data comprises determining a model of a heat map for at least a portion of the object during object generation;

and

and in which identifying a feature of the object which is associated with a predicted object generation temperature below a fusing temperature of build material to be used in object generation comprises identifying a region of the heat map which is below a threshold temperature.

5. The method of claim 1 in which the modification data comprises object model modification data, the method further comprising:

determining initial modification data to increase a temperature of the feature in object generation;

modifying the object model data with the initial modification data to generate modified object model data;

analysing, using at least one processor, the modified object model data; and

determining, using at least one processor and from said analysing, if a feature generated according to the modified object model data is associated with a predicted object generation temperature which is below a fusing temperature of build material to be used in object generation, if so, determining, using at least one processor, further modification data to be used in object generation, the further modification data being to increase the temperature of the feature during object generation.

6. The method of claim 1 in which the modification data comprises object model modification data, the modification data being to increase a volume of the object in a locality of the feature.

7. The method of claim 6 in which the modification data is to increase a size of the feature.

8. The method of claim 1 in which the modification data comprises control data to change an amount of print agent to be applied to build material to increase energy absorption in a locality of the feature.

9. The method of claim 1 further comprising generating control data based on the object model data and the modification data.

10. The method of claim 9 further comprising generating an object using the control data.

11. Apparatus comprising at least one processor, the at least one processor comprising:

a heat analysis module to analyse object model data representing an object to be generated by an additive manufacturing apparatus, to generate a temperature distribution model indicative of a predicted temperature distribution within the object during object generation, and to identify any feature of the object associated with a predicted temperature which is below a fusing temperature of build material to be used in object generation; and

a modification data module to determine modification data, wherein the modification data is indicative of a modification of at least one of the object model data and an object generation control parameter, the modification data being determined such that a temperature of an identified feature is predicted to be at least the fusing temperature of build material to be used in object generation.

12. Apparatus according to claim 11 in which the modification data module is to determine a modification which causes an increase in energy absorption in a locality of the feature during object generation.

13. Apparatus according to claim 11 further comprising a control data module to generate control data using the object model data and the modification data.

14. Apparatus according to claim 13 further comprising additive manufacturing apparatus to generate an object according to the control data.

15. A machine readable medium comprising instructions which, when executed by a processor, cause the processor to:

analyse object model data representing an object to be generated by an additive manufacturing apparatus;

generate a model of a temperature distribution within the object during object generation;

identify if any feature of the object is associated with a temperature which is below a fusing temperature of build material to be used in object generation; and

determine modification data, the modification data being to enhance fusion of the feature in object generation by modifying at least one of;

a material distribution within the object to be generated; and

a energy absorption characteristic of the object in object generation.