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Build-to-Last: Strength to Weight 3D Printed Objects

Lu, L, Sharf, A, Zhao, H, Wei, Y, Fan, Q, Chen, X, Savoye, Y, Tu, C, Cohen-Or, D and Chen, B (2014) Build-to-Last: Strength to Weight 3D Printed Objects. ACM Transactions On Graphics, 33 (4). ISSN 0730-0301

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The emergence of low-cost 3D printers steers the investigation of new geometric problems that control the quality of the fabricated object. In this paper, we present a method to reduce the material cost and weight of a given object while providing a durable printed model that is resistant to impact and external forces. We introduce a hollowing optimization algorithm based on the concept of honeycomb-cells structure. Honeycombs structures are known to be of minimal material cost while providing strength in tension. We utilize the Voronoi diagram to compute irregular honeycomb-like volume tessellations which define the inner structure. We formulate our problem as a strength–to–weight optimization and cast it as mutually finding an optimal interior tessellation and its maximal hollowing subject to relieve the interior stress. Thus, our system allows to build-to-last 3D printed objects with large control over their strength-to-weight ratio and easily model various interior structures. We demonstrate our method on a collection of 3D objects from different categories. Furthermore, we evaluate our method by printing our hollowed models and measure their stress and weights.

Item Type: Article
Additional Information: © ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions On Graphics, VOL33, ISS4, 01/07/2014 http://dx.doi.acm.org/10.1145/2601097.2601168
Uncontrolled Keywords: 0801 Artificial Intelligence and Image Processing, 0806 Information Systems
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Computer Science & Mathematics
Publisher: Association for Computing Machinery
Related URLs:
Date Deposited: 24 Oct 2019 09:00
Last Modified: 04 Sep 2021 08:36
DOI or ID number: 10.1145/2601097.2601168
URI: https://researchonline.ljmu.ac.uk/id/eprint/11623
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