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Research Papers

Additive Manufacturing Constraints in Topology Optimization for Improved Manufacturability

[+] Author and Article Information
Kunal Mhapsekar

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

Matthew McConaha

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

Sam Anand

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

1Corresponding author.

Manuscript received September 19, 2017; final manuscript received January 24, 2018; published online March 7, 2018. Assoc. Editor: Johnson Samuel.

J. Manuf. Sci. Eng 140(5), 051017 (Mar 07, 2018) (16 pages) Paper No: MANU-17-1592; doi: 10.1115/1.4039198 History: Received September 19, 2017; Revised January 24, 2018

Additive manufacturing (AM) provides tremendous advantage over conventional manufacturing processes in terms of creative freedom, and topology optimization (TO) can be deemed as a potential design approach to exploit this creative freedom. To integrate these technologies and to create topology optimized designs that can be easily manufactured using AM, manufacturing constraints need to be introduced within the TO process. In this research, two different approaches are proposed to integrate the constraints within the algorithm of density-based TO. Two AM constraints are developed to demonstrate these two approaches. These constraints address the minimization of number of thin features as well as minimization of volume of support structures in the optimized parts, which have been previously identified as potential concerns associated with AM processes such as powder bed fusion AM. Both the manufacturing constraints are validated with two case studies each, along with experimental validation. Another case study is presented, which shows the combined effect of the two constraints on the topology optimized part. Two metrics of manufacturability are also presented, which have been used to compare the design outputs of conventional and constrained TO.

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Figures

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Fig. 2

Flowchart of the algorithm for density based TO with SIMP

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Fig. 3

Elements and layers in sample design space

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Fig. 4

Single-layer primary neighborhood of element e

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Fig. 5

A case of an element near the boundary of the design space and its primary neighborhood

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Fig. 6

A case of an element at the boundary of a feature and its primary neighborhood Ne

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Fig. 7

Algorithm for density mapping in the thin feature constraint

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Fig. 8

Primary neighborhood Ne and a sample secondary neighborhood Nij

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Fig. 9

Combined effect of primary and secondary neighborhoods—effective neighborhood size

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Fig. 10

Flowchart of the modified algorithm for constrained TO with density mapping approach

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Fig. 12

Depiction of the approach to calculate support structure volume required for an element

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Fig. 13

Flowchart of the modified algorithm for constrained TO with multi-objective approach

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Fig. 14

Ray tracing approach to determine thin features

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Fig. 15

A sample part with voxel-based support structures

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Fig. 16

Design space and boundary conditions for cantilever beam test case

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Fig. 18

Results of structural and manufacturability analysis for the unconstrained TO of cantilever beam

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Fig. 19

Results of structural and manufacturability analysis for the constrained TO of cantilever beam

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Fig. 20

Design space and boundary conditions for L-bracket test case

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Fig. 22

Results of structural and manufacturability analysis for the unconstrained TO of lamp bracket

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Fig. 23

Results of structural and manufacturability analysis for the constrained TO of lamp bracket

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Fig. 24

Design space and boundary conditions for cantilever beam test case

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Fig. 25

TO outputs for different weights for compliance and support volume (element representation)

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Fig. 26

TO outputs for different weights for compliance and support volume (iso-surface representation)

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Fig. 27

Comparing the volume of support structures for unconstrained and constrained TO

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Fig. 28

Comparative results of static structural analysis of the optimized parts

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Fig. 29

Design space and boundary conditions for lateral bracket test case

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Fig. 30

TO outputs for different weights for compliance and support volume (element representation)

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Fig. 31

TO outputs for different weights for compliance and support volume (iso-surface representation)

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Fig. 32

Comparing the volume of support structures for unconstrained and constrained TO

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Fig. 33

Comparative results of static structural analysis of the optimized parts

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Fig. 34

Results of structural and manufacturability analysis for the multiconstrained TO of cantilever beam

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