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research-article

Additive Manufacturing Constraints in Topology Optimization for Improved Manufacturability

[+] Author and Article Information
Kunal Mhapsekar

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

Matthew McConaha

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

Sam Anand

Center for Global Design and Manufacturing, Department of Mechanical and Materials Engineering, University of Cincinnati, Cincinnati, Ohio 45221
sam.anand@uc.edu

1Corresponding author.

ASME doi:10.1115/1.4039198 History: Received September 19, 2017; Revised January 24, 2018

Abstract

Additive manufacturing (AM) provides tremendous advantage over conventional manufacturing processes in terms of creative freedom and topology optimization 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 topology optimization process. In this research, two different approaches are proposed to integrate the constraints within the algorithm of density based topology optimization. Two additive manufacturing 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 additive manufacturing (PBFAM). 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 topology optimization.

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