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PAPERS: Multimaterial Design Methods for AM

Design and Manufacturing Functionally Gradient Material Objects With an Off the Shelf Three-Dimensional Printer: Challenges and Solutions

[+] Author and Article Information
Anthony Garland

Department of Mechanical Engineering,
Clemson University,
Clemson, SC 29634
e-mail: apg@clemson.edu

Georges Fadel

Department of Mechanical Engineering,
Clemson University,
Clemson, SC 29634
e-mail: fgeorge@clemson.edu

Contributed by the Design for Manufacturing Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received February 20, 2015; final manuscript received July 15, 2015; published online October 12, 2015. Assoc. Editor: David Rosen.

J. Mech. Des 137(11), 111407 (Oct 12, 2015) (11 pages) Paper No: MD-15-1157; doi: 10.1115/1.4031097 History: Received February 20, 2015; Revised July 15, 2015

This paper presents the challenges and solutions encountered while designing and then printing functionally gradient material (FGM) objects using an off the shelf fused deposition modeling (FDM) 3D printer. The printer, Big Builder Dual-Feed Extruder from 3dprinter4u, Noordwijkerhout, The Netherlands, has the unique design of extruding two different filaments out of one nozzle. By controlling the rate at which the two filaments are pulled into the melt chamber, FGM objects can be printed. Software challenges associated with process planning required to print an FGM object are solved by showing a method for printing a discretized gradient and by designing an open-loop control mechanism for the extruder motors. A design method is proposed that models an object using a level-set function (LSF) with a material gradient. Instead of merely identifying the boundaries of the object, the level set also models the material gradient within the object. This representation method along with a genetic algorithm finds an optimal design for an FGM cantilever beam that is then printed on the FDM printer. The model and genetic algorithm are also used to solve a standard topology optimization problem. The results are compared to a similar FGM topology optimization method in the literature. All the codes for this paper are made open source to facilitate future research.

Copyright © 2015 by ASME
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References

Figures

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Fig. 1

Big Builder Extruder head

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Fig. 2

Simplified rendering of the Extruder head

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Fig. 3

Dark PLA transitioning to a lighter PLA. Uneven mixing from back (left) to front (right).

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Fig. 4

Cross section rendering of the melt chamber. Uneven mixing within the chamber causes stripes to be printed and uneven mixing from back to front of a single object.

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Fig. 5

Discretized gradient workflow

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Fig. 6

Functional gradient discretized into 11 regions

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Fig. 7

Three-dimensional printed bar with discretized gradient (139.7 mm × 25.4 mm × 12.7 mm)

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Fig. 8

Response test example. The change ratio command was given at the arrow on the far left. The first visual detection of change is at the middle arrow. A 100% change is at the arrow on the far right.

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Fig. 9

Open-loop controller sends the change ratio commands 2.52 mm3 ahead of time

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Fig. 10

A 50 × 100 mm gradient rectangle printed using the open-loop controller

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Fig. 11

Percent composition of PLA in the front extruder for the object in Fig. 10

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Fig. 12

Level-set model for 1D FGM beam

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Fig. 13

Optimal design for a cantilever beam using six control points

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Fig. 14

LSF overlaid on top of the manufactured FGM beam. PLA is at φ=0. Nylon is at φ=1. Nylon has a lighter color.

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Fig. 15

Optimal design for a cantilever beam using 11 control points

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Fig. 16

MMB truss design problem

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Fig. 17

(Upper) The LSF is modeled in 3D With the isocurve shown in black. (Lower) The level-set function projection into the XY plane is shown.

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Fig. 18

Design with w1 = 0.25. (Top) The LSF where the dots show the XY position of the control points. (Bottom) Optimal design showing percentage PLA at each point.

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