Big picture context: Technology democratization Ubiquity of 3D - - PowerPoint PPT Presentation

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Big picture context: Technology democratization Ubiquity of 3D - - PowerPoint PPT Presentation

Jan 13, 2024 148 likes •440 views

The Modern CAD/CAM Workflow: Scan, Design, Edit, Analyze, and Fabricate Without Triangles Duane Storti Mechanical Engineering University of Washington Seattle, WA Big picture context: Technology democratization Ubiquity of 3D imaging

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The Modern CAD/CAM Workflow:

Scan, Design, Edit, Analyze, and Fabricate Without Triangles

Duane Storti Mechanical Engineering University of Washington Seattle, WA

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“Big picture” context: Technology democratization

  • Ubiquity of 3D imaging (CT, MR, …)

democratizing volumetric scanning

  • CUDA democratizing parallel computing
  • 3D printing democratizing manufacturing
  • Near a threshold where:

“If you can think/imagine it, you can build it.”

  • Chris Anderson (Wired), Walt Disney, Lego?
  • But can you model “it” with current computer-aided

design (CAD) software?

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Motivational problems

  • Designing “Bigfoot”
  • Current models/algorithms scale badly
  • Boundary representations (b-reps)/triangulations
  • Sculptured surfaces  lots of patches/triangles
  • Boolean ops scale with product of triangle counts
  • Modeling bones with pins crashed CAD systems
  • Solution: Hack the 3D printer build set-up
  • Designing/printing objects with graded properties
  • Brain phantom, graded octet truss
  • Crucial advantage of 3D printing (additive mfg.)
  • B-reps ill-suited for describing interior composition
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Brain Phantom: Graded radiological activity (Solution: Test page hack)

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Graded Octet Truss via Vat Photo-Polymerization (Solution: Hack the build stack)

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Need better software for interacting with image stack models (and less hackery!)

  • Interactive tools for
  • Viewing, Editing, Boolean operations
  • Modeling of graded material properties
  • Analysis
  • Preparation for 3D printing
  • GPU-based parallel computing with CUDA

enables live interaction with new approach:

  • Voxel SDF-reps (Models are image stacks!)
  • Irony alert!

GPU Technology built to render triangles beautifully, saves the day when there are no triangles…

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Voxel SDF-rep Image Stack Modeler

  • CUDA/Python Implementation by Chris Uchytil

using:

  • Pyopengl
  • Pycuda: graphics interop
  • Numba: bulk of CUDA code including kernels
  • Pyside: user interface
  • Demonstrations recorded in real-time
  • n workstation with GTX 1080
  • Demo videos: Triangle free!
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Import bones from CT (and label file). Perform basic modeling ops.

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Import bones, adjust spacing, and construct union

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Creating Voxel SDF-reps: torus, cylinder, pin

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Pinned bones: uniform material

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Pinned bones: unions with properties

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Modeling Ops: Swept Solids

C implementation By Di Zhang

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Modeling Ops: Skeletal Editing

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How? And why without triangles?

What do you value?

  • As a rendering, this is ??? _
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How? Why without triangles?

What do you value?

  • As a rendering, this is beautiful
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How? Why without triangles?

What do you value?

  • As a rendering, this is beautiful
  • As a solid model, it is ??? _
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How? Why without triangles?

What do you value?

  • As a rendering, this is beautiful
  • As a solid model, it is broken!

What is inside/outside?

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Limitations of Current CAD Systems

Primarily boundary representation (B-rep)

  • Robustness issues
  • Limited support for variable material
  • Difficult to import scanned objects
  • Leads to “Bigfoot” crashes!
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Classify points as in/out by function evaluation Signed Distance Functions (SDFs) very desirable: (1) Simplified root finding (2) Skeletal editing Can we create functions and/or SDFs for: (1) Real engineering parts? (2) Parts captured via scan?

Alternative approach: Implicit or Function-based (f-rep) models

Coordinates F-rep Sphere SDF-rep Sphere Cartesian x2 + y 2 + z 2 – R2 < 0 𝑦2 + 𝑧2 + 𝑨2 – R < 0 Spherical r 2 – R2 < 0 r – R < 0

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F-rep for Engineering Part: by Mark Ensz

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F-rep for Engineering Part: Hex Nut

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Engineering Part: F-rep wood screw

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SDF-reps (Signed Distance Functions)

  • Few analytic SDF primitives
  • Compute voxelized approximation of SDF
  • Create “label” file
  • Sample sign of F-rep on grid
  • Segmentation of 3D imaging
  • Convert label file to grid of SDF values
  • 3D distance transform
  • Upwind differencing (scheme used in level set methods)
  • Interpolate as needed (wavelets)
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Issues on the 3D printing end of the workflow

  • Convert models to STL files
  • De facto standard for 3D printing
  • Bag of triangles  Lots of problems/limitations
  • Need to slice STL to determine layer descriptions
  • Instead use voxel SDF-rep
  • Model is an image stack
  • Send images to printer as slice descriptions
  • Variable material  Auxiliary property stack
  • Use grayscale or color images to encode materials
  • New operations on inhomogeneous objects
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Take-away points

  • Advances on the design side (CAD software) are

essential to realize the potential of 3D printing.

  • Implicit approaches are helpful and link directly to

Image stack/Voxel methods that provide:

  • Straightforward modeling of graded materials/properties
  • Unified format for 3D operations:

scan, design, analyze and fabricate

  • Real-time interactivity using GPU-based parallelism
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References

[1] Yurtoglu, M., GPU-based Parallel Computation of Integral Properties of Volumetrically Digitized Objects, PhD Dissertation, University of Washington, 2017. [2] Peterson, G., Schwartz, J., Zhang, D., Weiss, B., Ganter,M., Storti, D. and Boydston, AJ. Production of Materials with Spatially-Controlled Crosslink Density via Vat Photopolymerization, ACS Applied Materials & Interfaces. 8, 29037−29043 (2016). DOI:10.1021/acsami.6b09768 [3] Zhang, D., A GPU Accelerated Signed Distance Voxel Modeling System, PhD Dissertation, University of Washington, 2016. [4] Storti, D, and Yurtoglu, M., CUDA for Engineers: An Introduction to High-Performance Parallel Computing, Addison-Wesley Professional, NY, 2015. [5] Storti D, Ganter MA, Ledoux WR, Ching RP, Hu Y, Haynor D. Wavelet SDF-Reps: Solid Modeling With Volumetric Scans. ASME. International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Volume 6: 33rd Design Automation Conference, Parts A and B (2007):501-513. doi:10.1115/DETC2007-34703. [6] Storti, D., Ganter, M., Ledoux, W., Ching, R., Hu, Y., and Haynor, D. Artifact vs. Anatomy: Dealing With Conflict of Geometric Modeling Descriptions. No. 2007-01-2450. SAE Technical Paper, (2007). [7] Mark T. Ensz, Duane W. Storti, and Mark A. Ganter, Implicit Methods for Geometry Creation, Int. J.

  • Comput. Geom. Appl. 08, 509 (1998).

DOI: http://dx.doi.org/10.1142/S0218195998000266

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Acknowledgments/Thanks

  • Students (Current and Former UW AM lab members)
  • Chris Uchytil (code and videos), Ben Weiss
  • Mete Yurtoglu (Google), Di Zhang (Bodylabs), Mark Ensz (Sandia)
  • Siu Kwan Lam (Continuum Analytics) – Numba support
  • UW Colleagues:
  • Mark Ganter (AM Lab Co-director)
  • Nick Boechler Lab (ME), AJ Boydston Lab (Chemistry)
  • Bil Ledoux (VA) – motivation/sample data/support
  • Mike Miller (U. Indiana Med. School, Siemens,…)
  • UW College of Engineering (Strategic Research Initiative Program)
  • Ricoh
  • NVIDIA
  • Thank you for your attention!