Transfer learning/dictionary generation and usage for tailored part parameter generation from coupon builds

Patent metadata

Field	Value
Publication number	US-11079739-B2
Application number	US-201916284409-A
Country	US
Kind code	B2
Filing date	Feb 25, 2019
Priority date	Feb 25, 2019
Publication date	Aug 3, 2021
Grant date	Aug 3, 2021

Abstract

According to some embodiments, system and methods are provided comprising receiving, via a communication interface of a part parameter dictionary module comprising a processor, geometry data for a plurality of geometric structures forming a plurality of parts, wherein the parts are manufactured with an additive manufacturing machine; determining, using the processor of the part parameter dictionary module, a feature set for each geometric structure; generating, using the processor of the part parameter dictionary module, one of a coupon and a coupon set for the feature set; generating an optimized parameter set for each coupon, using the processor of the part parameter dictionary module, via execution of an iterative learning control process for each coupon; mapping, using the processor of the part parameter dictionary module, one or more parameters of the optimized parameter set to one or more features of the feature set; and generating a dictionary of optimized scan parameter sets to fabricate geometric structures with a material used in additive manufacturing. Numerous other aspects are provided.

First claim

The invention claimed is:

1. A method comprising:
receiving, via a communication interface of a part parameter dictionary module comprising a processor, geometry data for a plurality of geometric structures represented when forming a plurality of parts, wherein the received geometry data represents geometric structures in unspecified parts and the parts are manufactured with an additive manufacturing machine;
determining, using the processor of the part parameter dictionary module, a feature set for each geometric structure;
fabricating, using the processor of the part parameter dictionary module, one of a coupon and a coupon set for the feature set, wherein each coupon is a representative test sample of the feature set for each geometric structure;
generating an optimized parameter set for each coupon, using the processor of the part parameter dictionary module, via execution of an iterative learning control process for each coupon;
mapping, using the processor of the part parameter dictionary module, one or more parameters of the optimized parameter set to one or more features of the feature set; and
generating a dictionary of optimized scan parameter sets to fabricate geometric structures with a material used in additive manufacturing.

2. The method of claim 1 , wherein a feature set is one or more features, and wherein a feature is one or more structural aspects of the part.

3. The method of claim 2 , wherein the feature set includes at least one of thermal leakage, voxel size, scan direction, hatch spacing, and thermal lag.

4. The method of claim 1 , wherein the parameter set includes at least one of laser power, scan speed, laser spot size, layer thickness and hatch spacing.

5. The method of claim 1 , wherein each entry in the dictionary comprises part-specific geometries associated with a specific build model.

6. The method of claim 5 , further comprising:
receiving, at the part parameter dictionary module, a request for a scan parameter set for the part having a 3D geometry;
decomposing the part into one or more geometric structures;
assigning each of the geometric structures to one or more voxels;
receiving, at the dictionary, a request including the one or more assigned voxels;
generating, using the processor of the part parameter dictionary module, an optimized parameter set for the one or more assigned voxels; and
outputting the optimized parameters in a scan file to the additive manufacturing machine to produce the part.

7. The method of claim 6 , wherein the optimized parameter set is generated via application of a transfer learning algorithm.

8. A system comprising:
a part parameter dictionary module including a processor; and
a memory storing program instructions, the part parameter dictionary module operative with the program instructions to perform the functions as follows:
receive geometry data for a plurality of geometric structures represented when forming a plurality of parts, wherein the received geometry data represents geometric structures in unspecified parts and the parts are manufactured with an additive manufacturing machine;
determine a feature set for each geometric structure;
fabricate one of a coupon and a coupon set for the feature set, wherein each coupon is a representative test sample of the feature set for each geometric structure;
generate an optimized parameter set for each coupon via execution of an iterative learning control process for each coupon;
map one or more parameters of the optimized parameter set to one or more features of the feature set;
generate a dictionary of optimized scan parameter sets to fabricate geometric structures with a material used in additive manufacturing.

9. The system of claim 8 , wherein a feature set is one or more features, and wherein a feature is one or more structural aspects of the part.

10. The system of claim 9 , wherein the feature set includes at least one of thermal leakage, voxel size, scan direction, hatch spacing, and thermal lag.

11. The system of claim 8 , wherein the parameter set includes at least one of laser power, scan speed, laser spot size, layer thickness and hatch spacing.

12. The system of claim 8 , wherein each entry in the dictionary comprises part-specific geometries associated with a specific build model.

13. The system of claim 12 , further comprising program instructions to:
receive, at the part parameter dictionary module, a request for a scan parameter set for the part having a 3D geometry;
decompose the part into one or more geometric structures;
assign each of the geometric structures to one or more voxels;
receive, at the dictionary, a request including the one or more assigned voxels;
generate an optimized parameter set for the one or more assigned voxels; and
output the optimized parameters in a scan file to the additive manufacturing machine to produce the part.

14. The system of claim 13 , wherein the optimized parameter set is generated via application of a transfer learning algorithm.

15. A non-transitory computer-readable medium storing instructions that, when executed by a computer processor, cause the computer processor to perform a method comprising:
receiving, via a communication interface of a part parameter dictionary module comprising a processor, geometry data for a plurality of geometric structures represented when forming a plurality of parts, wherein the received geometry data represents geometric structures in unspecified parts and the parts are manufactured with an additive manufacturing machine;
determining, using the processor of the part parameter dictionary module, a feature set for each geometric structure;
fabricating, using the processor of the part parameter dictionary module, one of a coupon and a coupon set for the feature set, wherein each coupon is a representative test sample of the feature set for each geometric structure;
generating an optimized parameter set for each coupon, using the processor of the part parameter dictionary module, via execution of an iterative learning control process for each coupon;
mapping, using the processor of the part parameter dictionary module, one or more parameters of the optimized parameter set to one or more features of the feature set; and
generating a dictionary of optimized scan parameter sets to fabricate geometric structures with a material used in additive manufacturing.

16. The medium of claim 15 , wherein each entry in the dictionary comprises part-specific geometries associated with a specific build model.

17. The medium of claim 16 , further comprising:
receiving, at the part parameter dictionary module, a request for a scan parameter set for the part having a 3D geometry;
decomposing the part into one or more geometric structures;
assigning each of the geometric structures to one or more voxels;
receiving, at the dictionary, a request including the one or more assigned voxels;
generating, using the processor of the part parameter dictionary module, an optimized parameter set for the one or more assigned voxels; and
outputting the optimized parameters in a scan file to the additive manufacturing machine to produce the part.

18. The system of claim 15 , wherein the parameter set includes at least one of laser power, scan speed, laser spot size, layer thickness and hatch spacing.

19. The medium of claim 15 , wherein the feature set includes at least one of thermal leakage, voxel size, scan direction, hatch spacing, and thermal lag.

20. The medium of claim 15 , wherein the optimiz

Assignees

• Gen Electric

Inventors

• Roychowdhury Subhrajit
• Chen Alexander
• Ping Xiaohu
• Hershey John Erik

Classifications

• B22F12/90

  Means for process control, e.g. cameras or sensors · CPC title

• B22F10/36

  of energy beam parameters · CPC title

• B22F10/28

  Powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM] · CPC title

• B33Y10/00

  Processes of additive manufacturing · CPC title

• G05B2219/49018

  Laser sintering of powder in layers, selective laser sintering SLS · CPC title