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
Your Session has timed out. Please sign back in to continue.


Sobczak, J. J., and Drenchev, L., 2013, “Metallic Functionally Graded Materials: A Specific Class of Advanced Composites,” J. Mater. Sci. Technol., 29(4), pp. 297–316. [CrossRef]
Cui, W., and Wisnom, M., 1993, “A Combined Stress-Based and Fracture-Mechanics-Based Model for Predicting Delamination in Composites,” Composites, 24(6), pp. 467–474. [CrossRef]
Tymrak, B., Kreiger, M., and Pearce, J., 2014, “Mechanical Properties of Components Fabricated With Open-Source 3-D Printers Under Realistic Environmental Conditions,” Mater. Des., 58, pp. 242–246. [CrossRef]
Garland, A., Mocko, G., and Fadel, G., 2014, “Challenges in Designing and Manufacturing Fully Optimized Functional Gradient Material Objects,” ASME Paper No. DETC2014-34544.
Blouin, V. Y., Oschwald, M., and Hu, Y., 2005, “Design of Functionally Graded Structures for Enhanced Thermal Behavior,” ASME Paper No. DETC2005-85290.
Kou, X., and Tan, S., 2007, “Heterogeneous Object Modeling: A Review,” Comput. Aided Des., 39(4), pp. 284–301. [CrossRef]
Kou, X., and Tan, S., 2005, “A Hierarchical Representation for Heterogeneous Object Modeling,” Comput. Aided Des., 37(3), pp. 307–319. [CrossRef]
Ozbolat, I. T., and Khoda, A., 2014, “Design of a New Parametric Path Plan for Additive Manufacturing of Hollow Porous Structures With Functionally Graded Materials,” ASME J. Comput. Inf. Sci. Eng., 14(4), p. 041005. [CrossRef]
Rozvany, G. I. N., 2009, “A Critical Review of Established Methods of Structural Topology Optimization,” Struct. Multidiscip. Optim., 37(3), pp. 217–237. [CrossRef]
Cansizoglu, O., Harrysson, O. L., and West, H. A., II, 2008, “Applications of Structural Optimization in Direct Metal Fabrication,” Rapid Prototyping J., 14(2), pp. 114–122. [CrossRef]
Sigmund, O., 2001, “A 99 Line Topology Optimization Code Written in matlab ,” Struct. Multidiscip. Optim., 21(2), pp. 120–127. [CrossRef]
Hiller, J. D., and Lipson, H., 2009, “Multi-Material Topological Optimization of Structures and Mechanisms,” 11th Annual Conference on Genetic and Evolutionary Computation (GECCO '09), pp. 1521–1528.
Huang, J., and Fadel, G. M., 2000, “Heterogeneous Flywheel Modeling and Optimization,” Mater. Des., 21(2), pp. 111–125. [CrossRef]
Kou, X., and Tan, S., 2007, “A Systematic Approach for Integrated Computer-Aided Design and Finite Element Analysis of Functionally-Graded-Material Objects,” Mater. Des., 28(10), pp. 2549–2565. [CrossRef]
Kou, X., and Tan, S., 2008, “Heterogeneous Objects Modelling and Applications,” Springer-Verlag, Berlin, pp. 42–59.
Kou, X., Parks, G., and Tan, S., 2012, “Optimal Design of Functionally Graded Materials Using a Procedural Model and Particle Swarm Optimization,” Comput. Aided Des., 44(4), pp. 300–310. [CrossRef]
Cho, J., and Ha, D., 2002, “Optimal Tailoring of 2D Volume-Fraction Distributions for Heat-Resisting Functionally Graded Materials Using FDM,” Comput. Methods Appl. Mech. Eng., 191(29), pp. 3195–3211. [CrossRef]
Cho, J., and Ha, D., 2002, “Volume Fraction Optimization for Minimizing Thermal Stress in NiAl2O3 Functionally Graded Materials,” Mater. Sci. Eng., A, 334(1), pp. 147–155. [CrossRef]
Ramani, A., 2011, “Multi-Material Topology Optimization With Strength Constraints,” Struct. Multidiscip. Optim., 43(5), pp. 597–615. [CrossRef]
Xia, Q., and Wang, M. Y., 2008, “Simultaneous Optimization of the Material Properties and the Topology of Functionally Graded Structures,” Comput. Aided Des., 40(6), pp. 660–675. [CrossRef]
Gao, T., and Zhang, W., 2010, “Topology Optimization Involving Thermo-Elastic Stress Loads,” Struct. Multidiscip. Optim., 42(5), pp. 725–738. [CrossRef]
Wang, M. Y., and Wang, X., 2004, “ “Color” Level Sets: A Multi-Phase Method for Structural Topology Optimization With Multiple Materials,” Comput. Methods Appl. Mech. Eng., 193(6), pp. 469–496. [CrossRef]
Cho, J., and Shin, S., 2004, “Material Composition Optimization for Heat-Resisting FGMs by Artificial Neural Network,” Composites, Part A, 35(5), pp. 585–594. [CrossRef]
Hu, Y., Blouin, V. Y., and Fadel, G. M., 2008, “Design for Manufacturing of 3D Heterogeneous Objects With Processing Time Consideration,” ASME J. Mech. Des., 130(3), p. 031701. [CrossRef]
Vaezi, M., Chianrabutra, S., and Mellor, B., 2013, “Multiple Material Additive manufacturing—Part 1: A Review: This Review Paper Covers a Decade of Research on Multiple Material Additive Manufacturing Technologies Which Can Produce Complex Geometry Parts With Different Materials,” Virtual Phys. Prototyping, 8(1), pp. 19–50. [CrossRef]
Shin, K., Natu, H., and Dutta, D., 2003, “A Method for the Design and Fabrication of Heterogeneous Objects,” Mater. Des., 24(5), pp. 339–353. [CrossRef]
Morvan, S., Fadel, G. M., and Love, J., 2001, “Manufacturing of a Heterogeneous Flywheel on a LENS Apparatus,” 12th Solid Freeform Fabrication Symposium, Austin, TX, Aug. 8–10, pp. 553–560.
Bruyas, A., Geiskopf, F., and Renaud, P., 2014, “Towards Statically Balanced Compliant Joints Using Multimaterial 3D Printing,” ASME Paper No. DETC2014-34532.
Keating, S., and Oxman, N., 2013, “Compound Fabrication: A Multi-Functional Robotic Platform for Digital Design and Fabrication,” Rob. Comput. Integr. Manuf., 29(6), pp. 439–448. [CrossRef]
Es-Said, O., Foyos, J., and Noorani, R., 2000, “Effect of Layer Orientation on Mechanical Properties of Rapid Prototyped Samples,” Mater. Manuf. Processes, 15(1), pp. 107–122. [CrossRef]
Vega, V., Clements, J., and Lam, T., 2011, “The Effect of Layer Orientation on the Mechanical Properties and Microstructure of a Polymer,” J. Mater. Eng. Perform., 20(6), pp. 978–988. [CrossRef]
Ranellucci, A., “Slic3r,” http://Slic3r.Org
Setoodeh, S., Abdalla, M., and Gürdal, Z., 2005, “Combined Topology and Fiber Path Design of Composite Layers Using Cellular Automata,” Struct. Multidiscip. Optim., 30(6), pp. 413–421. [CrossRef]
Vermaak, N., Michailidis, G., and Parry, G., 2014, “Material Interface Effects on the Topology Optimization of Multi-Phase Structures Using a Level Set Method,” Struct. Multidiscip. Optim., 50(4), pp. 623–644. [CrossRef]
Adam, G. A., and Zimmer, D., 2014, “Design for Additive Manufacturing—Element Transitions and Aggregated Structures,” CIRP J. Manuf. Sci. Technol., 7(1), pp. 20–28. [CrossRef]
Garland, A., 2015, “Source Code,” https://Github.Com/Garland3/clemsonPhD


Grahic Jump Location
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.

Grahic Jump Location
Fig. 1

Big Builder Extruder head

Grahic Jump Location
Fig. 2

Simplified rendering of the Extruder head

Grahic Jump Location
Fig. 3

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

Grahic Jump Location
Fig. 5

Discretized gradient workflow

Grahic Jump Location
Fig. 6

Functional gradient discretized into 11 regions

Grahic Jump Location
Fig. 7

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

Grahic Jump Location
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.

Grahic Jump Location
Fig. 15

Optimal design for a cantilever beam using 11 control points

Grahic Jump Location
Fig. 16

MMB truss design problem

Grahic Jump Location
Fig. 12

Level-set model for 1D FGM beam

Grahic Jump Location
Fig. 13

Optimal design for a cantilever beam using six control points

Grahic Jump Location
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.

Grahic Jump Location
Fig. 9

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

Grahic Jump Location
Fig. 10

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

Grahic Jump Location
Fig. 11

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

Grahic Jump Location
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.

Grahic Jump Location
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.



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