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Research Papers

Integration of Design for Manufacturing Methods With Topology Optimization in Additive Manufacturing

[+] Author and Article Information
Rajit Ranjan

Center for Global Design and Manufacturing,
Department of Mechanical and
Materials Engineering,
University of Cincinnati,
Cincinnati, OH 45221
e-mail: ranjanrt@mail.uc.edu

Rutuja Samant

Center for Global Design and Manufacturing,
Department of Mechanical and
Materials Engineering,
University of Cincinnati,
Cincinnati, OH 45221
e-mail: samantrv@mail.uc.edu,

Sam Anand

Center for Global Design and Manufacturing,
Department of Mechanical and
Materials Engineering,
University of Cincinnati,
Cincinnati, OH 45221
e-mail: sam.anand@uc.edu

1Corresponding author.

Manuscript received February 6, 2016; final manuscript received November 8, 2016; published online January 25, 2017. Assoc. Editor: Xiaoping Qian.

J. Manuf. Sci. Eng 139(6), 061007 (Jan 25, 2017) (14 pages) Paper No: MANU-16-1094; doi: 10.1115/1.4035216 History: Received February 06, 2016; Revised November 08, 2016

Additive manufacturing (AM) processes are used to fabricate complex geometries using a layer-by-layer material deposition technique. These processes are recognized for creating complex shapes which are difficult to manufacture otherwise and enable designers to be more creative with their designs. However, as AM is still in its developing stages, relevant literature with respect to design guidelines for AM is not readily available. This paper proposes a novel design methodology which can assist designers in creating parts that are friendly to additive manufacturing. The research includes formulation of design guidelines by studying the relationship between input part geometry and AM process parameters. Two cases are considered for application of the developed design guidelines. The first case presents a feature graph-based design improvement method in which a producibility index (PI) concept is introduced to compare AM friendly designs. This method is useful for performing manufacturing validation of pre-existing designs and modifying it for better manufacturability through AM processes. The second approach presents a topology optimization-based design methodology which can help designers in creating entirely new lightweight designs which can be manufactured using AM processes with ease. Application of both these methods is presented in the form of case studies depicting design evolution for increasing manufacturability and associated producibility index of the part.

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Figures

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Fig. 3

Re-coater arm movement

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Fig. 4

Sample bracket with supports

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Fig. 5

(a) Internal angle and offsetting, (b) thin region detection, and (c) detection of thin openings

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Fig. 6

Flowchart for contour offset algorithm

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Fig. 7

Hollow cylinder: (a) facet requiring support and (b) facet touching support

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Fig. 8

Flowchart for triangular facet algorithm

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Fig. 9

Algorithm for making feature graph

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Fig. 10

Representative feature graph

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Fig. 11

Sample part for feature graph

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Fig. 12

Feature graph for sample part

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Fig. 13

Support elements for (a) nonboundary element, (b) boundary element with six bottom elements, and (c) boundary element with four bottom elements

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Fig. 14

Plot for penalty function

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Fig. 15

Flowchart for DFAM topology optimization

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Fig. 16

Process of design evolution

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Fig. 17

Design 1 for heat exchanger

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Fig. 18

Design 2 for heat exchanger

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Fig. 19

Bicycle pedal: (a) design iteration1, (b) design iteration2, and (c) design iteration3

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Fig. 20

Problem definition for cantilever beam

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Fig. 21

(a) Topology optimization result, (b) design for cantilever beam, and (c) design with support

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Fig. 22

(a) Results for constrained topology optimization process, (b) 3D model for design, and (c) support structures

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Fig. 23

Deformation results for (a) standard top. opt. and (b) constrained top. opt.

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Fig. 24

Design space and loading conditions for case study 4

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Fig. 25

(a) Results for standard topology optimization process, (b) 3D model for design, and (c) support structures

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Fig. 26

(a) Results for constrained topology optimization process, (b) 3D model for design, and (c) support structures

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Fig. 27

Deformation results for (a) standard top. opt. and (b) constrained top. opt.

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