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Digital Material Design Using Tensor-Based Error Diffusion for Additive Manufacturing

Title:

Digital Material Design Using Tensor-Based Error Diffusion for Additive Manufacturing

Leung, Yuen-Shan, Kwok, Tsz-Ho ORCID: https://orcid.org/0000-0001-7240-1426, Mao, Huachao and Chen, Yong (2019) Digital Material Design Using Tensor-Based Error Diffusion for Additive Manufacturing. Computer-Aided Design, 114 . pp. 224-235. ISSN 00104485

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Official URL: http://dx.doi.org/10.1016/j.cad.2019.05.031

Abstract

Recent multi-material additive manufacturing (AM) technologies enable the fabrication of an object with accurate deposition of different types of materials. Hence, in addition to geometric shapes, it is possible to use different material compositions to optimize the mechanical properties of a component for given design requirements. However, current AM processes have a limitation on the number of materials that can be deposited during the fabrication process. Due to the constraint, it is critical to optimize the material distribution using the limited base materials; however, an extremely large design space exists in a design domain that is enabled by the AM technologies. In this paper, we introduce a digital material design framework to generate digital material compositions that can be printed and be able to achieve the desired behavior. We take analog material composition as the input and perform the analog-to-digital conversion using an exemplar-based approach based on a pre-computed material library. The patterns in the library are constructed with different combinations of the given base materials, and their mechanical properties are computed using finite element simulation. Accordingly, the design goal of the analog-to-digital conversion is to find material composition in the design domain with matching mechanical properties. A tensor-based error diffusion algorithm has been developed to reduce the approximation error during the conversion effectively. Experimental tests based on the design framework have been performed. The test results demonstrate that our framework can quickly find effective solutions for various multi-material design problems.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical, Industrial and Aerospace Engineering
Item Type:Article
Refereed:Yes
Authors:Leung, Yuen-Shan and Kwok, Tsz-Ho and Mao, Huachao and Chen, Yong
Journal or Publication:Computer-Aided Design
Date:2019
Funders:
  • National Science Foundation (NSF)
  • Epstein Institute
Digital Object Identifier (DOI):10.1016/j.cad.2019.05.031
Keywords:Additive manufacturing, Digital material design, Error diffusion, Tensor, Robotic grasper
ID Code:985968
Deposited By: TSZ HO KWOK
Deposited On:11 Feb 2020 17:00
Last Modified:11 Feb 2020 17:00
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