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Research Papers

A Reverse Compensation Framework for Shape Deformation Control in Additive Manufacturing

[+] Author and Article Information
Kai Xu, Tsz-Ho Kwok, Zhengcai Zhao

Epstein Department of Industrial and
Systems Engineering,
University of Southern California,
Los Angeles, CA 90089

Yong Chen

Epstein Department of Industrial and
Systems Engineering,
University of Southern California,
Los Angeles, CA 90089
e-mail: yongchen@usc.edu

1Corresponding author.

Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received July 22, 2016; final manuscript received August 28, 2016; published online February 16, 2017. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 17(2), 021012 (Feb 16, 2017) (9 pages) Paper No: JCISE-16-2026; doi: 10.1115/1.4034874 History: Received July 22, 2016; Revised August 28, 2016

Shape deformation is a well-known problem in additive manufacturing (AM). For example, in the stereolithography (SL) process, some of the factors that lead to part deformation including volumetric shrinkage, thermal cooling, added supporting structures, and the layer-by-layer building process. Variant sources of deformation and their interactions make it difficult to predict and control the shape deformation to achieve high accuracy that is comparable to numerically controlled machining. In this paper, a computational framework based on a general reverse compensation approach is presented to reduce the shape deformation in AM processes. In the reverse compensation process, the shape deformation is first calculated by physical measurements. A novel method to capture the physical deformation by finding the optimal correspondence between the deformed shape and the given nominal model is presented. The amount of compensation is determined by a compensation profile that is established based on nominal and offset models. The compensated digital model can be rebuilt using the same building process for a part with significantly less part deformation than the built part related to the nominal model. Two test cases have been performed to demonstrate the effectiveness of the presented computational framework. There is a 40–60% improvement in terms of L2- and L-norm measurements on geometric errors.

Copyright © 2017 by ASME
Topics: Deformation , Shapes
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Figures

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Fig. 1

An example of a physical object built by the MIP-SL process that deforms when compared to the nominal shape

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Fig. 2

Deformation sources

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Fig. 3

A computational framework to reduce shape deformation in AM processes

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Fig. 4

Models with no salient feature points (a) nominal CAD model and (b) built physical model

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Fig. 5

Cross-parameterization of two models with 35 artificial markers

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Fig. 6

Schematic of modified letter H part

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Fig. 7

Built object of the modified letter H model

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Fig. 8

Sample points of the nominal model and the corresponding points on the physical model

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Fig. 9

Simple bar test part with double thickness

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Fig. 10

Offset models and built physical parts

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Fig. 11

Comparisons of deformation of models without offset and with offsets

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Fig. 12

Compensated profile

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Fig. 13

Compensated STL model

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Fig. 14

Comparisons of deformation before and after compensation

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Fig. 15

Comparison of physical built parts: (a) original part and (b) part with compensation

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Fig. 16

Testcase 2: (a) nominal model and (b) scan model with markers

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Fig. 17

Comparison of baseline nominal model and scan model compensation: (a) comparison of entire model and (b) magnified views of two sections

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Fig. 18

Physical built parts of offset models

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Fig. 19

Deformation using offset models: (a) offset outward model and (b) offset inward model

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Fig. 20

Compensation: (a) compare with nominal model and (b) compensated STL model

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Fig. 21

Physical parts comparisons: (a) without compensation and (b) with compensation

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Fig. 22

Deformation of built part with compensation: (a) comparison of entire model and (b) magnified views of two sections

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