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PAPERS: Multimaterial Design Methods for AM

A Generalized Optimality Criteria Method for Optimization of Additively Manufactured Multimaterial Lattice Structures

[+] Author and Article Information
Tino Stanković

Engineering Design and Computing Laboratory,
Department of Mechanical and Process Engineering,
ETH Zürich,
Tannenstr. 3, 8092 Zürich, Switzerland
e-mail: tinos@ethz.ch

Jochen Mueller

Mem. ASME
Engineering Design and Computing Laboratory,
Department of Mechanical and Process Engineering,
ETH Zürich,
Tannenstr. 3, 8092 Zürich, Switzerland
e-mail: jm@ethz.ch

Paul Egan

Mem. ASME
Engineering Design and Computing Laboratory,
Department of Mechanical and Process Engineering,
ETH Zürich,
Tannenstr. 3, 8092 Zürich, Switzerland
e-mail: pegan@ethz.ch

Kristina Shea

Mem. ASME
Engineering Design and Computing Laboratory,
Department of Mechanical and Process Engineering,
ETH Zürich,
Tannenstr. 3, 8092 Zürich, Switzerland
e-mail: kshea@ethz.ch

1Corresponding author.

Early iterations of this work were accepted to the 2015 ASME Computers and Information in Engineering Conference (Stanković et al. 2015).Contributed by the Design for Manufacturing Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received February 15, 2015; final manuscript received June 15, 2015; published online October 12, 2015. Assoc. Editor: Timothy W. Simpson.

J. Mech. Des 137(11), 111405 (Oct 12, 2015) (12 pages) Paper No: MD-15-1126; doi: 10.1115/1.4030995 History: Received February 15, 2015; Revised June 15, 2015

Recent progress in additive manufacturing (AM) allows for printing customized products with multiple materials and complex geometries that could form the basis of multimaterial designs with high performance and novel functions. Effectively designing such complex products for optimal performance within the confines of AM constraints is challenging due to the need to consider fabrication constraints while searching for optimal designs with a large number of variables, which stem from new AM capabilities. In this study, fabrication constraints are addressed through empirically characterizing multiple printed materials' Young's modulus and density using a multimaterial inkjet-based 3D-printer. Data curves are modeled for the empirical data describing two base printing materials and 12 mixtures of them as inputs for a computational optimization process. An optimality criteria (OC) method is developed to search for solutions of multimaterial lattices with fixed topology and truss cross section sizes. Two representative optimization studies are presented and demonstrate higher performance with multimaterial approaches in comparison to using a single material. These include the optimization of a cubic lattice structure that must adhere to a fixed displacement constraint and a compliant beam lattice structure that must meet multiple fixed displacement constraints. Results demonstrate the feasibility of the approach as a general synthesis and optimization method for multimaterial, lightweight lattice structures that are large-scale and manufacturable on a commercial AM printer directly from the design optimization results.

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Figures

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Fig. 1

DfAM product design methodology

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Fig. 2

Results of benchmarking algorithms for a steel lattice test-case

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Fig. 3

Empirical AM data for Young's modulus as a function of density. Shown are the experimentally obtained values (rectangle), the values taken from the materials' datasheets (circle), and the fitted curve.

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Fig. 4

Cubic cell definition

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Fig. 5

Cube lattice topology and boundary conditions

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Fig. 6

Displacement constraint definition for cubic lattice

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Fig. 10

Cantilever beam boundary conditions and constraints

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Fig. 14

Cantilever beam in plane displacement results for the x1 i = 3000 MPa starting point. The allowed displacement range is shown with two parallel lines per each constrained node pair.

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