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

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 optimized parameter set is generated via application of a transfer learning algorithm.