Research Papers

Direct Geometry Processing for Telefabrication

[+] Author and Article Information
Yong Chen

Industrial and Systems Engineering,
University of Southern California,
Los Angeles, CA 90089
e-mail: yongchen@usc.edu

Kang Li

e-mail: kli@iit.edu

Xiaoping Qian

Mechanical, Materials and
Aerospace Engineering,
Illinois Institute of Technology,
Chicago, IL 60616
e-mail: qian@iit.edu

Contributed by the Computers and Information Division of ASME for publication in the Journal of Computers and Information Science IN Engineering. Manuscript received November 2, 2012; final manuscript received May 29, 2013; published online August 19, 2013. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 13(4), 041002 (Aug 19, 2013) (15 pages) Paper No: JCISE-12-1199; doi: 10.1115/1.4024912 History: Received November 02, 2012; Revised May 29, 2013

This paper presents a new approach for telefabrication where a physical object is scanned in one location and fabricated in another location. This approach integrates three-dimensional (3D) scanning, geometric processing of scanned data, and additive manufacturing (AM) technologies. In this paper, we focus on a set of direct geometric processing techniques that enable the telefabrication. In this approach, 3D scan data are directly sliced into layer-wise contours. Sacrificial supports are generated directly from the contours and digital mask images of the objects and the supports for stereolithography apparatus (SLA) processes are then automatically generated. The salient feature of this approach is that it does not involve any intermediate geometric models such as STL, polygons, or nonuniform rational B-splines (NURBS) that are otherwise commonly used in prevalent approaches. The experimental results on a set of objects fabricated on several SLA machines confirm the effectiveness of the approach in faithfully telefabricating physical objects.

Copyright © 2013 by ASME
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Bailey, M. J., 1995, “Tele-Manufacturing: Rapid Prototyping on the Internet,” Comput. Graph. Appl., 15(6), pp. 20–26. [CrossRef]
Jiang, P. Y., and Fukuda, S., 1999, “Internet Service and Maintenance for rRP-Oriented Tele-Manufacturing,” Concurr. Eng., 7(3), pp. 179–189. [CrossRef]
Lan, H., Chin, K. S., and Hong, J., 2005, “Development of a Tele-Service System for RP Service Bureaus,” Rapid Prototyping J., 11(2), pp. 98–105. [CrossRef]
Luo, R. C., Lee, W. Z., Chou, J. H., and Leong, H. T., 1999, “Telecontrol of Rapid Prototyping Machine via Internet for Automated Tele-Manufacturing. In Oboticsand Automation,” Proceedings of 1999 IEEE International Conference, Vol. 3, pp. 2203–2208.
Luo, R. C., and Tzou, J. H., 2004, “The Development of an Intelligent Web-Based Rapid Prototyping Manufacturing System,” IEEE Trans. Autom. Sci. Eng., 1(1), pp. 4–13. [CrossRef]
Marsan, A., Kumar, V., Dutta, D., and Pratt, M. J., 1998, “An Assessment of Data Requirements and Data Transfer Formats for Layered Manufacturing,” NIST, U.S. Department of Commerce.
Liu, G. H., Wong, Y. S., Zhang, Y. F., and Loh, H. T., 2003, “Modelling Cloud Data for Prototype Manufacturing,” J. Mater. Process. Technol., 38(1), pp. 53–57. [CrossRef]
Wu, Y. F., Wong, Y. S., Loh, H. T., and Zhang, Y. F., 2004, “Modelling Cloud Data Using an Adaptive Slicing Approach,” Computer-Aided Design, 36(3), pp. 231–240. [CrossRef]
Park, H. T., Chang, M. H., and Park, S. C., 2007, “A Slicing Algorithm of Point Cloud for Rapid Prototyping,” Proceedings of the 2007 Summer Computer Simulation Conference, Society for Computer Simulation International, p. 24.
Shin, H., Park, S., and Park.E., 2004, “Direct Slicing of a Point Set Model for Rapid Prototyping,” Computer-Aided Design and Applications, 1(1–4), pp. 109–115. Available at: http://cadanda.homestead.com/V1Nos1to4_13.pdf.
Javidrad, F., and Pourmoayed, A. R., 2011, “Contour Curve Reconstruction From Cloud Data for Rapid Prototyping,” Rob. Comput.-Integr. Manuf., 27(2), pp. 397–404. [CrossRef]
Yang, P., Schmidt, T., and Qian., X., 2010, “Direct Digital Design and Manufacturing From Massive Point-Cloud Data,” Comput.-Aided Des. Appl., 6(5), pp. 685–699.
Yang, P., and Qian, X., 2008, “Adaptive Slicing of Moving Least Squares Surfaces: Toward Direct Manufacturing From Point Cloud Data,” ASME Trans. J. Comput. Inf. Sci. Eng., 8(3), pp. 433–442. [CrossRef]
Yang, P., Li, K., and Qian, X., 2011, “Topologically Enhanced Slicing of MLS Surfaces,” ASME J. Comput. Inf. Sci. Eng., 11(3), p. 031003. [CrossRef]
Amenta, N., and Kil, Y. J., 2004, “Defining Point-Set Surfaces,” ACM Trans. Graph., 23(3), pp. 264–270. [CrossRef]
Hart, J. C., 1998, “Morse Theory for Implicit Surface Modeling,” Mathematical Visualization, H.-C.Hege, and K.Polthier, eds., Springer-Verlag, Berlin/Vienna/New York, pp. 257–268.
Pauly, M., Keiser, R., Kobbelt, L. P., and Gross, M., 2003, “Shape Modeling With Point-Sampled Geometry,” ACM Trans. Graph., 22(3), pp. 641–650. [CrossRef]
Yang, P., and Qian, X., 2009, “Direct Boolean Intersection Between Acquired and Designed Geometry,” Comput.-Aided Des., 41(2), pp. 81–94. [CrossRef]
Zhang, D., Yang, P., and Qian, X., 2009, “Adaptive NC Path Generation From Massive Point Data With Bounded Error,” ASME Trans. J. Manuf. Sci. Eng., 131(1), p. 011001. [CrossRef]
Amenta, N., and Kil, Y. J., 2004, “The Domain of a Point Set Surface,” Proceedings of 2004 IEEE/Eurographics Symposium on Point-Based Graphics, pp. 139–147.
Hopkinson, N., R.Hague, and P.Dickens, 2006, Rapid Manufacturing: An Industrial Revolution for the Digital Age, John Wiley & Sons, West Suessex PO19 8SQ, England.
Beaman, J. J., Barlow, J., Bourell, D. L., Crawford, R. H., Marcus, H. L., and McAlea, K. P., 1997, Solid Freeform Fabrication: A New Direction in Manufacturing, Springer, New York.
Allen, S., and Dutta, D., 1995, “Determination and Evaluation of Support Structures in Layered Manufacturing,” J. Des. Manuf., 5, pp. 153–162. [CrossRef]
Hur, J., and Lee, K., 1996, “Efficient Algorithm for Automatic Support Structure Generation in Layered Manufacturing,” ASME Computers in Engineering Conference, Irvine, CA, Aug. 18–22, Paper No. DETC96/1324.
Kulkarni, P., Marsan, A., and Dutta, D., 2000, “A Review of Process Planning Techniques in Layered Manufacturing,” Rapid Prototyping J., 6(1), pp. 18–35. [CrossRef]
Chalasani, K., Jones, L., and Roscoe, L., 1995, “Support Generation for Fused Deposition Modeling,” Proceedings of Solid Freeform Fabrication Symposium, Austin, Texas.
Chen, Y., and Wang, C. C. L., 2011, “Uniform Offsetting of Polygonal Model Based on Layered Depth-Normal Images,” Comput.-Aided Des., 43(1), pp. 31–46. [CrossRef]
Wang, C. C. L., Leung, Y., and Chen, Y., 2010, “Solid Modeling by Layered Depth-Normal Images on the GP,” Comput.-Aided Des., 42(6), pp. 535–544. [CrossRef]
Zhao, H., Wang, C. C. L., Chen, Y., and Jin, X., 2011, “Parallel and Efficient Boolean on Polygonal Solids,” Vis. Comput., 27(6-8), pp. 507–517. [CrossRef]
Chen, Y., and Wang, C. C. L., 2010, “Contouring of Structured Points With Small Features,” ASME Computers and Information in Engineering Conference, Montreal, Quebec, Canada, Aug. 15–18, Paper No. DETC2010-29094.
Schneider, P. J., and Eberly, D. H., 2003, Geometric Tools for Computer Graphics, Morgan Kaufmann, San Francisco, CA.
Du, Q., Faber, V., and Gunzburger, M., 1999, “CentroidalVoronoi Tessellations: Applications and Algorithms,” SIAM Rev., 41(4), pp. 637–676. [CrossRef]
Du, Q., and Wang, D., 2006, “Recent Progress in Robust and Quality Delaunay Mesh Generation,” J. Comput. Appl. Math., 195(1), pp. 8–23. [CrossRef]
Zhou, C., Chen, Y., and Waltz, R. A., 2009, “Optimized Mask Image Projection for Solid Freeform Fabrication,” ASME J. Manuf. Sci. Eng., 131(6), p. 061004. [CrossRef]
Zhou, C., and Chen, Y., 2009, “Calibrating Large-Area Mask Projection Stereolithography for Its Accuracy and Resolution Improvements,” Proceedings of Solid Freeform Fabrication Symposium, Austin, Texas.
Xu, K., and Chen, Y., 2012, “Mask Image Planning for Deformation Control in Projection-Based Stereolithography Process,” ASME Computers and Information in Engineering Conference, Chicago, IL, Aug. 12–15, Paper No. DETC2012-71523.
Zhou, C., Chen, Y., Yang, Z., and Khoshnevis, B., 2013, “Digital Material Fabrication Using Mask-Image-Projection-Based Stereolithography,” Rapid Prototyping J., 19(3), pp. 153–165. [CrossRef]
Pan, Y., Zhou, C., and Chen, Y., 2012, “A Fast Mask Projection Stereolithography Process for Fabricating Digital Models in Minutes,” ASME J. Manuf. Sci. Eng., 134(5), p. 051011. [CrossRef]
Network of Excellence Aim@Shape, http://www.aimatshape.net
Besl, P. J., and McKay, N. D., 1992, “A Method for Registration of 3-D Shapes,” IEEE Trans. Pattern Anal. Mach. Intell., 14(2), pp. 239–256. [CrossRef]


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Fig. 1

Overview of telefabrication: a physical object is scanned in one location and fabricated in another location. The scan data are processed according to the given machine specifications from micro- to mesoscales.

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Fig. 2

Direct geometric processing for telefabrication. The physical part in (a) is scanned in Chicago and the scanned data cloud is shown in (b). The data cloud is then sliced as shown in (c). Upon transferring the data to Los Angeles, support structures (d) are automatically generated from the sliced model and a physical part is built as shown in (e).

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Fig. 3

A digitization system and software system

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Fig. 4

The six scanning steps with 60-deg step angle

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Fig. 5

Overview of the Morse complex based point-cloud slicing procedure. (a) point cloud. (b) Morse function on the MLS surface. (c) critical point generation. (d) Morse-Smale complex. (e) enhanced Reeb graph. (f) sliced model. The magenta, green, and yellow and white Dots represent the maximum, (top and bottom) saddle, and minimum critical points, respectively.

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Fig. 6

Critical points and slicing topology change

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Fig. 7

Morse-Smale complex and enhanced Reeb graph of a mechanical part. (a) Morse-Smale complex with ascending and descending integral lines; (b) enhanced Reeb graph extracted from the complex.

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Fig. 9

Identify the slice’s topology by intersecting the slicing plane with the enhanced Reeb graph. (a) and (d) slicing planes; (b) and (e) intersecting with the enhanced Reeb graph; (c) and (f) adaptive contour marching.

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Fig. 10

Adaptive contour marching. (a) intersection-based marching with adaptive step length; (b) step length determined by osculating circle radius; (c) partial point cloud near the slicing plane; and (d) contour points generated by marching with curvature-adaptive step lengths.

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Fig. 11

Marching cube based MLS surface slicing. (a) slicing plane (yellow) and points (red) close to the plane; (b) front view; (c) marching cube grid on the slicing plane; (d) zoom- in view; (e) g(x) field; (f) three extracted zero-value contours; (g) zoom-in view only the middle contour (green, thick) is taken as the slicing contour; (h) output contour for the current slicing plane.

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Fig. 12

Slicing with topological guarantee. (a) another slicing plane where two contours are expected; (b) zoom-in view; (c) scalar field; (d) six contours extracted; (e) contours zoom-in; (f) two contours picked as actual slice contours.

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Fig. 13

An illustration of the angle-based support generation method

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Fig. 14

An illustration of various geometries and related supports. (a) Cantilever; (b) vaulted overhang; and (c) small overhang.

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Fig. 15

An illustration of the contour-based support generation method. (a) Given layers and (b) layer analysis result.

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Fig. 16

An example of layer 107. (a) Previous layer; (b) current layer; and (c) computing result.

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Fig. 17

An example of support layout based on region covering. (a) Input regions to be supported; (b) computed support layouts; (c) CAD model of generated supports; (d) CAD model of generated supports by the Lightyear system.

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Fig. 18

Telefabrication test 1: fertility model. (a) Scanned point-cloud data; (b) critical points and Morse complex; (c) enhanced Reeb graph; (d) sliced model; (e) built part.

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Fig. 19

Telefabrication test 2: sculpture model at original orientation. (a) Scanned point-cloud data; (b) sliced model; (c) generated supports; and (d) display of both point clouds and supports.

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Fig. 20

Test 2: sculpture model at a different orientation with fabrication machine A (layer thickness = 0.01 mm). (a) Scanned point-cloud data; (b) sliced model; (c) generated supports; and (d) built part with attached supports structure.

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Fig. 21

Raw scan data with outlier removed. (a) Six step-scan range images; (b) Six registered triangle meshes; and (c) raw scan data

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Fig. 22

Geometric data flow in the intermediate steps of telefabrication.

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Fig. 23

Face features comparison of sliced model and built part for two preprocessed slicing input.

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Fig. 24

Comparison between physical object and built part 1




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