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

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 (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?

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

Brain Phantom: Graded radiological activity (Solution: Test page hack)

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

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…

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 on workstation with GTX 1080 • Demo videos: Triangle free!

Import bones from CT (and label file). Perform basic modeling ops.

Import bones, adjust spacing, and construct union

Creating Voxel SDF-reps: torus, cylinder, pin

Pinned bones: uniform material

Pinned bones: unions with properties

Modeling Ops: Swept Solids C implementation By Di Zhang

Modeling Ops: Skeletal Editing

How? And why without triangles? What do you value?  As a rendering, this is ??? _

How? Why without triangles? What do you value?  As a rendering, this is beautiful

How? Why without triangles? What do you value?  As a rendering, this is beautiful  As a solid model, it is ??? _

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?

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!

Alternative approach: Implicit or Function-based (f-rep) models Classify points as in/out by function evaluation Coordinates F-rep Sphere SDF-rep Sphere 𝑦 2 + 𝑧 2 + 𝑨 2 – R < 0 x 2 + y 2 + z 2 – R 2 < 0 Cartesian r 2 – R 2 < 0 r – R < 0 Spherical 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?

F-rep for Engineering Part: by Mark Ensz

F-rep for Engineering Part: Hex Nut

Engineering Part: F-rep wood screw

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)

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

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

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

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!