Research Papers

Photocuring Temperature Study for Curl Distortion Control in Projection-Based Stereolithography

[+] Author and Article Information
Kai Xu

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.

Manuscript received February 23, 2016; final manuscript received July 18, 2016; published online August 24, 2016. Assoc. Editor: Donggang Yao.

J. Manuf. Sci. Eng 139(2), 021002 (Aug 24, 2016) (14 pages) Paper No: MANU-16-1121; doi: 10.1115/1.4034305 History: Received February 23, 2016; Revised July 18, 2016

Polymerization shrinkage and thermal cooling effect have been identified as two major factors that lead to the curl distortion in the stereolithography apparatus (SLA) process. In this paper, the photocuring temperature during the building process of mask image projection-based stereolithography (MIP-SL) and how it affects parts' curl distortion are investigated using a high-resolution infrared (IR) camera. Test cases of photocuring layers with different shapes, sizes, and layer thicknesses have been designed and tested. The experimental results reveal that the temperature increase of a cured layer is mainly related to the layer thickness, while the layer shapes and sizes have little effect. The photocuring temperatures of built layers using different exposure strategies including varying exposure time, grayscale levels, and mask image patterns have been studied. The curl distortions of a test case based on various exposure strategies have been measured and analyzed. It is shown that, by decreasing the photocuring temperature of built layers, the exposure strategies using grayscale levels and mask image patterns can effectively reduce the curl distortion with the expense of increased building time. In addition to curl distortion control, the photocuring temperature study also provides a basis for the curl distortion simulation in the MIP-SL process.

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Fig. 1

A physical object built by the MIP-SL process with curl distortion

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Fig. 2

In situ temperature monitoring using an IR camera in MIP-SL

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Fig. 3

The one-layer experimental design and the test cases

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Fig. 4

The temperature distribution and layer thickness of the one-layer circle with R = 3 in: (a) maximum curing temperature in IR image, (b) temperature distribution along the centerline (top), and physical built layer (bottom), and (c) layer thicknesses measured on selected sample points

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Fig. 5

The temperature differences between overlapping areas of five test cases: (a) circles of R = 2 in. and R = 3 in., (b) circles of R = 1 in. and R = 2 in., (c) circle of R = 1 in. and square of L = 2 in., and (d) squares of L = 2 in. and L = 3 in.

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Fig. 6

Using an IR camera to in situ monitor the free-surface-based MIP-SL process

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Fig. 7

Dimensions of a built part (in mm)

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Fig. 8

Four sample points in a photocuring region and the temperature plot at cursor 1 for test case #1

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Fig. 9

Building sequence in MIP-SLA

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Fig. 10

Temperature plot of a building cycle at cursor 1

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Fig. 11

Temperature evolutions at four and three sampling points

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Fig. 12

Mean temperature plots of the test cases with (a) different widths and (b) different thicknesses

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Fig. 13

Workflow of testing various exposure times on the maximum curing temperature

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Fig. 14

Photocuring temperature using different exposure times

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Fig. 15

Comparisons of the maximum curing temperatures using varying exposure time

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Fig. 16

Examples of grayscale mask images

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Fig. 17

Photocuring temperature using different grayscale levels exposures

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Fig. 18

Grayscale effects on curing temperature

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Fig. 19

Grayscale effects on curing time

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Fig. 20

Mask images of (a) mask pattern 1, (b) mask pattern 2, and (c) entire region

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Fig. 21

Photocuring temperature using mask patterns with different exposure times

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Fig. 22

Curing temperature of using grayscale 190

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Fig. 23

Curing temperature of grayscale 255 for 40 s

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Fig. 24

Curing temperature of mask pattern exposure

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Fig. 26

Schematic of curl distortion measurement

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Fig. 27

Simulation result of baseline part




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