0
Research Papers

Mass Customization: Reuse of Digital Slicing for Additive Manufacturing

[+] Author and Article Information
Tsz-Ho Kwok

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

Hang Ye

Department of Industrial
and Systems Engineering,
University at Buffalo,
The State University of New York,
Buffalo, NY 14260
e-mail: hye2@buffalo.edu

Yong Chen

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

Chi Zhou

Department of Industrial
and Systems Engineering,
University at Buffalo,
The State University of New York,
Buffalo, NY 14260
e-mail: chizhou@buffalo.edu

Wenyao Xu

Department of Computer
Science and Engineering,
University at Buffalo,
The State University of New York,
Buffalo, NY 14260
e-mail: wenyaoxu@buffalo.edu

1Corresponding author.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received May 6, 2016; final manuscript received June 20, 2016; published online February 16, 2017. Assoc. Editor: Xiaoping Qian.

J. Comput. Inf. Sci. Eng 17(2), 021009 (Feb 16, 2017) (8 pages) Paper No: JCISE-16-1953; doi: 10.1115/1.4034010 History: Received May 06, 2016; Revised June 20, 2016

Additive manufacturing, also known as three-dimensional (3D) printing, enables production of complex customized shapes without requiring specialized tooling and fixture, and mass customization can then be realized with larger adoption. The slicing procedure is one of the fundamental tasks for 3D printing, and the slicing resolution has to be very high for fine fabrication, especially in the recent developed continuous liquid interface production (CLIP) process. The slicing procedure is then becoming the bottleneck in the prefabrication process, which could take hours for one model. This becomes even more significant in mass customization, where hundreds or thousands of models have to be fabricated. We observe that the customized products are generally in a same homogeneous class of shape with small variation. Our study finds that the slicing information of one model can be reused for other models in the same homogeneous group under a properly defined parameterization. Experimental results show that the reuse of slicing information has a maximum of 50 times speedup, and its utilization is dropped from more than 90% to less than 50% in the prefabrication process.

FIGURES IN THIS ARTICLE
<>
Copyright © 2017 by ASME
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Fig. 1

The state-of-the-art flow of prefabrication computation in additive manufacturing: (a) CAD model, (b) support generation, (c) contour slicing, (d) tool path planning, and (e) 3D-printed part

Grahic Jump Location
Fig. 2

Two tooth aligner models share 99% of similarity. The left is for phase 0–30 days, and the right is for phase 31–90 days.

Grahic Jump Location
Fig. 3

The overview of the reuse of slicing. (Top row) The traditional prefabrication pipeline first slices the input model and then generates the images from the slices. The bottleneck is the slicing process (shown in arrow under Slicing). (Bottom row) The proposed pipeline for slicing reuse by computing the mapping between the input models and transfer the slices from the slicing results, bypassing the slicing process.

Grahic Jump Location
Fig. 4

The capability of cross-parameterization is demonstrated by linear interpolating the positions of vertices between two input hand models at t = 0 and t = 1

Grahic Jump Location
Fig. 5

The mapping optimization constraining the mapping by fixing the height (i.e., z coordinate). The transferred slices are in-plane by the constrained mapping.

Grahic Jump Location
Fig. 6

The mask images in the top row are generated from the contours that are directly sliced on the model of teeth 1. Those in the bottom row are generated from the reused slices that are computed based on the mapping from teeth 1 to 2. The fabricated parts are shown in the right.

Grahic Jump Location
Fig. 7

The mask images in the top row are generated from the contours that are directly sliced on the model of hearing aid 1. Those in the bottom row are generated from the reused slices. The fabricated parts are shown in the right.

Grahic Jump Location
Fig. 8

Physical test cases: (a) digital models of aligners and (b) hearing aids, (c) printed aligners, and (d) hearing aids

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In