Research Papers

Toward the Control of the EP3D Printed Surface

[+] Author and Article Information
Alvaro J. Rojas Arciniegas

Assistant Professor
Department of Automatics and Electronics,
College of Engineering,
Universidad Autonoma de Occidente,
Calle 25 No. 115-85,
Cali 760030, Colombia
e-mail: ajrojas@uao.edu.co

Marcos Esterman

Associate Professor
Industrial and Systems Engineering,
Kate Gleason College of Engineering,
Rochester Institute of Technology,
81 Lomb Memorial Drive,
Rochester, NY 14623
e-mail: mxeeie@rit.edu

Juan C. Cockburn

Associate Professor
Computer Engineering,
Kate Gleason College of Engineering,
Rochester Institute of Technology,
83 Lomb Memorial Drive,
Rochester, NY 14623
e-mail: jcceec@rit.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 November 14, 2014; published online December 15, 2014. Assoc. Editor: David L. Bourell.

J. Manuf. Sci. Eng 137(2), 021012 (Apr 01, 2015) (10 pages) Paper No: MANU-14-1195; doi: 10.1115/1.4029184 History: Received April 15, 2014; Revised November 14, 2014; Online December 15, 2014

The extension of electrophotographic (EP) printing into the additive manufacturing space has been seen as a natural step for this technology; however, the self-insulating nature of the process has prevented the creation of structures beyond a limited number of layers where surface defects are evident. This paper examines two control strategies for EP-based three-dimensional (EP3D) printing that minimize the surface defects to obtain the accurate reproduction of the intended 3D geometry. The strategies rely not on material deposition control but rather on progressively compensating layer after layer for irregularities forming on the surface. This represents an important step toward the development and future commercialization of EP3D printing.

Copyright © 2015 by ASME
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Fig. 1

Schematic of the EP3D printing process

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Fig. 2

Schematic of the transfusing process

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Fig. 3

Failed attempts to perform EP3D printing using transfuse belt material as intermediate substrate: (a) Toner not fused to final substrate after going through fuser, (b) toner fused to the intermediate substrate while preheating to 130 °C, and (c) sample got caught in the fuser at layer 6

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Fig. 4

(a) Transfuse belt material after being used as intermediate substrate, (b) 14-layer sample, and (c) 100-layer sample

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Fig. 5

Ra evolution for 100-layer sample fused using transfuse belt material as intermediate substrate and compared to readings from samples using Mylar as intermediate substrate

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Fig. 6

100-layer samples constructed using Mylar as intermediate substrate: (a) 1 toner (M) at 100% fill and (b) 2 toner (CM) at 100% fill

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Fig. 7

Comparison of measured profiles for 100-layer samples: (top) 2 toner produced with Mylar interface and (bottom) 1 toner using belt interface

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Fig. 8

Flow diagram of the simulation algorithm with compensation

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Fig. 9

Simulated profiles of force and sample generated without compensation

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Fig. 10

Simulated profiles of force and sample generated with compensation

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Fig. 11

Comparison on Ra for 30 layers from simulated data with no compensation, with compensation and the measurements on sample fused face down

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Fig. 12

Imaging set up with Point Grey camera

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Fig. 13

Images of 100-layer 2-toner sample: (a) Original, (b) grayscale, histogram adjusted, and (c) compensation image extracted

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Fig. 14

Detailed image of the edge detection approach: (a) Original image illuminated from the bottom, (b) edges detected for this image only, (c) edges from eight images (eight illumination angles) fused, and (d) compensation image after applying morphological operators

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Fig. 15

(a) 30-layer sample fused face up imaged with a flatbed scanner, (b) 22.3 × 14.9 mm section of the 30-layer sample imaged using GelSight, (c) 8 × 8 mm detail, and (d) 3D reconstruction of the detail area




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