Research Papers

Finite Element Simulation of Localized Electrochemical Deposition for Maskless Electrochemical Additive Manufacturing

[+] Author and Article Information
Anne M. Brant

Department of Mechanical
and Materials Engineering,
University of Cincinnati, Cincinnati,
OH 45221-0072
e-mail: brantam@mail.uc.edu

Murali M. Sundaram

Department of Mechanical
and Materials Engineering,
University of Cincinnati, Cincinnati,
OH 45221-0072
e-mail: murali.sundaram@uc.edu

Abishek B. Kamaraj

Department of Mechanical
and Materials Engineering,
University of Cincinnati, Cincinnati,
OH 45221-0072
e-mail: balsamak@mail.uc.edu

1Corresponding author.

Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING. Manuscript received April 15, 2014; final manuscript received July 31, 2014; published online November 26, 2014. Assoc. Editor: Darrell Wallace.

J. Manuf. Sci. Eng 137(1), 011018 (Feb 01, 2015) (9 pages) Paper No: MANU-14-1208; doi: 10.1115/1.4028198 History: Received April 15, 2014; Revised July 31, 2014; Online November 26, 2014

Localized electrodeposition (LED) was explored as an additive manufacturing technique with high control over process parameters and output geometry. The effect of variation of process parameters and changing boundary conditions during the deposition process on the output geometry was observed through simulation and experimentation. Trends were found between specific process parameters and output geometries in the simulations; trends varied between linear and nonlinear, and certain process parameters such as voltage and interelectrode gap were found to have a greater influence on the output than others. The simulations were able to predict the output width of deposition of experiments in an error of 8–30%. The information gained from this research allows for greater understanding of LED output, so that it can potentially be applied as an additive manufacturing technique of complex three-dimensional (3D) parts on the microscale.

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Element death algorithm

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Fig. 2

Modeling method and input parameters

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Fig. 1

Summary of electrodeposition simulation process

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Fig. 4

Final result imported into Matlab with extracted output dimensions

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Fig. 5

Effects of varying tool width

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Fig. 6

Effects of varying tool width to gap ratio

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Fig. 7

Comparison of effects due to varying tool width and width to gap ratio

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Fig. 8

Effects of varying applied tool voltage

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Fig. 9

Effects of varying electrolyte concentration

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Fig. 10

Effects of varying duty cycle

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Fig. 13

Comparison of trends seen in simulation and experiments

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Fig. 11

Experimental setup

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Fig. 12

Superposition of simulation and experimental results



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