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US-12623410-B2 - Dynamic print infill adjustment for determined stress points

US12623410B2US 12623410 B2US12623410 B2US 12623410B2US-12623410-B2

Abstract

Embodiments of the disclosure provide systems and methods for implementing 3D printing to manufacture 3D print objects with dynamic adjustment of 3D print infill specifications based on determined regions of stress points in a given 3D device design. A disclosed method comprises receiving a 3D object design for a 3D device to be printed; determining, based on the 3D object design and a trained model, a region of the 3D object with a projected likelihood of human interaction above a threshold likelihood; and generating, based on the determined region of the 3D object, instructions to selectively adjust one or more print infill specifications at the region.

Inventors

  • Logan Bailey
  • Brian NARKINSKY
  • Wesley Ip
  • Zachary A. Silverstein
  • Alexandra M. Isaly

Assignees

  • INTERNATIONAL BUSINESS MACHINES CORPORATION

Dates

Publication Date
20260512
Application Date
20230802

Claims (20)

  1. 1 . A method comprising: receiving a 3D object design for a 3D object to be printed; determining, using image recognition data based on the 3D object design and a trained machine learning (ML) model, object-level appearance cues that indicate one or more regions of the 3D object with a projected likelihood of human interaction above a threshold likelihood, wherein the determining comprises: performing physical analysis to identify one or more stress points, break points, or simulation points within the one or more regions of the 3D object; and performing physical analysis to identify a projected mechanical stress threshold at the one or more stress points, break points, or simulation points within the one or more regions; and generating, based on the projected mechanical stress threshold at the one or more stress points, break points, or simulation points, instructions to adjust one or more print infill specifications within the one or more regions.
  2. 2 . The method of claim 1 , wherein receiving the 3D object design for the 3D object to be printed further comprises receiving a G-code file representing the 3D object to be printed.
  3. 3 . The method of claim 1 , wherein determining the object-level appearance cues further comprises performing physical analysis to identify an estimation of grasp affordance and human engagement within the one or more regions.
  4. 4 . The method of claim 1 , wherein the one or more stress points, break points, or simulation points within the one or more regions comprise at least one location of potential human engagement, human manipulation or grasp object.
  5. 5 . The method of claim 1 , wherein performing physical analysis operations to identify the one or more of stress points, break points, or simulation points further comprises identifying one or more of fulcrums, pivot points, and levers, to identify the projected mechanical stress threshold.
  6. 6 . The method of claim 1 , wherein determining the object-level appearance cues further comprises rendering applied pressure in a simulation at the identified regions with the projected mechanical stress threshold.
  7. 7 . The method of claim 1 , wherein determining, the object-level appearance cues further comprises rendering and processing a heatmap of the one or more regions to determine mechanical stress points above a defined threshold of the 3D print model.
  8. 8 . The method of claim 1 , wherein generating, based on determining the region of the 3D object, instructions to adjust one or more print infill specifications within the or more regions further comprises generating instructions to print within the or more regions, a given print infill pattern based on a determined performance level of the given print infill pattern with a given 3D print filament.
  9. 9 . The method of claim 1 , wherein generating the instructions to adjust one or more print infill specifications within the or more regions further comprises generating instructions to print a given print infill pattern with a selected print infill density within the one or more regions.
  10. 10 . The method of claim 1 , wherein generating the instructions to adjust one or more print infill specifications within the or more regions further comprises generating instructions to print one or a combination of one or more of a selected filament, a selected composite filament, a selected infill pattern or an infill density within the one or more regions.
  11. 11 . A system, comprising: a processor; and a memory, wherein the memory includes a computer program product configured to perform operations for implementing 3D printing to manufacture a 3D object, the operations comprising: determining, using image recognition data based on the 3D object design and a trained machine learning (ML) model, object-level appearance cues that indicate one or more regions of the 3D object with a projected likelihood of human interaction above a threshold likelihood, wherein the determining comprises: performing physical analysis to identify one or more stress points, break points, or simulation points within the one or more regions of the 3D object; and performing physical analysis to identify a projected mechanical stress threshold at the one or more stress points, break points, or simulation points within the one or more regions; and generating, based on the projected mechanical stress threshold at the one or more stress points, break points, or simulation points, instructions to adjust one or more print infill specifications within the one or more regions.
  12. 12 . The system of claim 11 , wherein receiving the 3D object design for the 3D object to be printed further comprises receiving a G-code file representing the 3D object to be printed.
  13. 13 . The system of claim 11 , wherein the one or more stress points, break points, or simulation points within the one or more regions comprise at least one location of potential human engagement, human manipulation or grasp object.
  14. 14 . The system of claim 11 , wherein performing physical analysis operations to identify the one or more of stress points, break points, or simulation points further comprises identifying one or more of fulcrums, pivot points, and levers, to identify the projected mechanical stress threshold.
  15. 15 . The system of claim 11 , wherein generating the instructions to adjust one or more print infill specifications within the or more regions further comprises generating instructions to print one or a combination of one or more of a selected filament, a selected composite filament, a selected infill pattern or an infill density within the one or more regions.
  16. 16 . A computer program product for implementing 3D printing to manufacture a 3D object, the computer program product comprising: a computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by one or more computer processors to perform an operation comprising: determining, using image recognition data based on the 3D object design and a trained machine learning (ML) model, object-level appearance cues that indicate one or more regions of the 3D object with a projected likelihood of human interaction above a threshold likelihood, wherein the determining comprises: performing physical analysis to identify one or more stress points, break points, or simulation points within the one or more regions of the 3D object; and performing physical analysis to identify a projected mechanical stress threshold at the one or more stress points, break points, or simulation points within the one or more regions; and generating, based on the projected mechanical stress threshold at the one or more stress points, break points, or simulation points, instructions to adjust one or more print infill specifications within the one or more regions.
  17. 17 . The computer program product of claim 16 , wherein receiving the 3D object design for the 3D object to be printed further comprises receiving a G-code file representing the 3D object to be printed.
  18. 18 . The computer program product of claim 16 , wherein the one or more stress points, break points, or simulation points within the one or more regions comprise at least one location of potential human engagement, human manipulation or grasp object.
  19. 19 . The computer program product of claim 16 , wherein performing physical analysis operations to identify the one or more of stress points, break points, or simulation points further comprises identifying one or more of fulcrums, pivot points, and levers, to identify the projected mechanical stress threshold.
  20. 20 . The computer program product of claim 16 , wherein generating the instructions to adjust one or more print infill specifications within the or more regions further comprises generating instructions to print one or a combination of one or more of a selected filament, a selected composite filament, a selected infill pattern or an infill density within the one or more regions.

Description

BACKGROUND The present invention relates to three-dimensional (3D) printing, and more specifically, methods and systems for implementing enhanced 3D printing including dynamically generating infill specifications at determined regions of potential stress points in a 3D object design. 3D printing or additive manufacturing is a process of making three-dimensional objects or devices from a digital file. Print infill specifications provide an internal structure of a 3D printed object or device referred to as 3D print infill, typically provided to save printing time and material usage, and to optimize part weight, strength, and printing time. Many different infill patterns exist including many different shapes. A 3D printing slicer software generates G-code to print a 3D model with a 3D printer; G-code is a widely used numerical control (NC) programming language. When designing 3D models and configuring infill design and density in 3D printing slicer software, often users must generate multiple G-code file iterations due to post print discovery of weak points in a given manufactured 3D object. A need exists for new techniques and systems to generate dynamic infill specifications unique to a determined region of potential stress points, related to factors such as grasp affordance and human manipulation tasks. SUMMARY Embodiments of the disclosure are directed to systems and methods for implementing 3D printing to manufacture 3D print objects with dynamic adjustment of 3D print infill specifications based on determined regions of stress points in a given 3D device design. A disclosed non-limiting computer implemented method comprises receiving a 3D object design for a 3D device to be printed; determining, based on the 3D object design and a trained model, a region of the 3D object with a projected likelihood of human interaction above a threshold likelihood; and generating, based on the determined region of the 3D object, instructions to selectively adjust one or more print infill specifications at the region. Other disclosed embodiments include a computer system and computer program product for implementing 3D printing to manufacture 3D print objects with dynamic adjustment of 3D print infill specifications based on determined stress points in a given 3D device design, implementing features of the above-disclosed method. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram of an example computer environment for use in conjunction with one or more disclosed embodiments for implementing enhanced 3D printing to manufacture 3D objects with dynamically adjusting infill specifications to print at an identified region; FIG. 2 is a block diagram of an example system for implementing enhanced 3D printing to manufacture 3D objects with dynamically adjusting infill specifications to print at an identified region of one or more embodiments of the present disclosure; FIG. 3 is a flow chart of an example operations of an example method for implementing enhanced printing to manufacture 3D objects with dynamically adjusting infill specifications to print at an identified region of one or more embodiments of the present disclosure; FIG. 4 is a flow chart of further example operations of an example method for dynamically adjusting infill specifications to print at identified regions of a given 3D print object of one or more embodiments of the present disclosure; FIG. 5 illustrates example 3D print infill patterns for dynamically adjusting infill specifications to print at identified regions of a given 3D print object of one or more embodiments of the present disclosure; FIG. 6 illustrates example 3D print infill patterns with different example densities for dynamically adjusting infill specifications to print at identified regions of a given 3D print object of one or more embodiments of the present disclosure; and FIG. 7 is a flow chart of an example method for dynamically adjusting infill specifications of one or more embodiments of the present disclosure. DETAILED DESCRIPTION Embodiments of the present disclosure provide systems and methods for implementing enhanced 3D printing to manufacture 3D objects with dynamically adjusting infill specifications (e.g., pattern, height, and density of infill) printed at an identified region of potential human interaction. Disclosed embodiments identify regions of potential human interaction, engagement or manipulation, and associated stress points, and break points, of a given 3D print object that are related to human scale manipulation tasks. In a disclosed embodiment, semantics or G-code print instructions related to print execution of infill specifications for a given 3D print object can be optimized in relation to factors such as grasp affordance and leverage break points. In a disclosed embodiment, a 3D print infill control module detects a region having potential break points and related mechanical stress thresholds based on projected human interaction with a region of a 3D pri