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Research Papers

Understanding Process Parameter Effects of RepRap Open-Source Three-Dimensional Printers Through a Design of Experiments Approach

[+] Author and Article Information
Antonio Lanzotti

Fraunhofer JL IDEAS,
Department of Industrial Engineering,
University of Naples Federico II,
P.leTecchio, 80,
Naples 80125, Italy
e-mail: antonio.lanzotti@unina.it

Massimo Martorelli

Fraunhofer JL IDEAS-CREAMI,
Department of Industrial Engineering,
University of Naples Federico II,
P.leTecchio, 80,
Naples 80125, Italy
e-mail: massimo.martorelli@unina.it

Gabriele Staiano

Fraunhofer JL IDEAS-CREAMI,
Department of Industrial Engineering,
University of Naples Federico II,
P.leTecchio, 80,
Naples 80125, Italy
e-mail: gabriele.staiano@unina.it

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 4, 2014; published online November 26, 2014. Assoc. Editor: Joseph Beaman.

J. Manuf. Sci. Eng 137(1), 011017 (Feb 01, 2015) (7 pages) Paper No: MANU-14-1207; doi: 10.1115/1.4029045 History: Received April 15, 2014; Revised November 04, 2014; Online November 26, 2014

With a view to enabling additive manufacturing (AM) processes, today, open-source, low-cost 3D printers are systems with great potential. However there is a significant lack of scientific data on the performance of open-source 3D systems and on the selection of adequate process parameters that can help to improve the quality of the parts. The purpose of this paper is to assess the effects of the main process parameters on the dimensional accuracy of a specific open-source 3D printer, the RepRap Prusa-Mendel I2. This study consisted of a benchmarking part, involving elementary shapes representing a series of different features. By means of a full factorial DoE (Design of Experiments), with three factors (layer thickness, deposition speed, and flow rate), three levels, and three replications, 81 parts were obtained. Subsequently, a laser scanner (D700 Laser Scanner—3Shape, Denmark) was used as high resolution reverse engineering system in order to evaluate the variation between real parts and nominal geometry. The impact of the main process parameters was evaluated and optimal combinations were analyzed. On the basis of the results obtained in the experiments, practical suggestions for the settings of common process parameters were formulated. Test results serve to improve the quality of AM parts through the most appropriate selection of the main process parameters.

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Figures

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Fig. 1

The open-source 3D printer used in this study: the Prusa Mendel I2

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Fig. 2

Logical work-flow for the comparison of benchmarking nominal and real parts fabricated following a full factorial design

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Fig. 3

Benchmarking part [21] with three replications of 10 main features used in the study

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Fig. 4

Poor quality part fabricated using a layer thickness of 0.05 mm

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Fig. 5

The acquisition of point clouds of benchmarking real part using D700 Laser Scanner

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Fig. 6

Alignment of the point clouds with the CAD model through the creation of three datum

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Fig. 7

Graphical evaluation of distances between point cloud and 3D CAD nominal model correlated to a RMS equal to 0.15

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Fig. 8

Pareto diagram of the main effects ranked according to decreasing contribution ratio (CR)

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Fig. 9

Main effects plot of the three process parameters (A,B,C) at three levels (−1,0,1) on the response RMS

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Fig. 10

Interaction plots of the three process parameters (A,B,C) at three levels (−1,0,1) on the response RMS

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