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Research Papers: Design for Manufacture and the Life Cycle

On the Geometric Accuracy of RepRap Open-Source Three-Dimensional Printer

[+] Author and Article Information
Antonio Lanzotti

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

Domenico Maria Del Giudice

Fraunhofer JL IDEAS-CREAMI,
Department of Industrial Engineering,
University of Naples Federico II,
P.le Tecchio, 80,
Naples 80125, Italy
e-mail: domenicomaria.delgiudice@unina.it

Antonio Lepore

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

Gabriele Staiano

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

Massimo Martorelli

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

1Corresponding author.

Contributed by the Design for Manufacturing Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received March 15, 2015; final manuscript received July 28, 2015; published online September 2, 2015. Assoc. Editor: Christopher Williams.

J. Mech. Des 137(10), 101703 (Sep 02, 2015) (8 pages) Paper No: MD-15-1216; doi: 10.1115/1.4031298 History: Received March 15, 2015; Revised July 28, 2015

In the field of additive manufacturing (AM) processes, there is a significant lack of scientific data on the performance of open-source 3D printers in relation to process parameter values. The purpose of this paper is to assess the impact of the main process parameters on the accuracy of a set of typical geometric features, as obtained with an open-source 3D printer, the RepRap Prusa-Mendel I2. For this purpose, a benchmarking part was set up, composed of elementary shapes, representing a series of different geometric features. By means of a DoE approach, it was possible to assess the effects of two process parameters—layer thickness (Lt) and flow rate (Fr)—on five geometric features: cube, sphere, cylinder, cone, and angled surface. A high resolution Laser Scanner was used to evaluate the variation between the acquired geometric feature and the corresponding 3D computer-aided design (CAD) nominal model. On the basis of experimental results, it was possible to analyze and discuss the main effects of the above-mentioned process parameters on each geometric feature. These results can help RepRap users in the correct selection of process parameters with the aim of improving the quality of prototypes.

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References

Jones, R. , Haufe, P. , Sells, E. , Iravani, P. , Olliver, V. , Palmer, C. , and Bowyer, A. , 2011, “ RepRap-The Replicating Rapid Prototyper,” Robotica, 29(1), pp. 177–191. [CrossRef]
ISO/ASTM 52915, 2013, Standard Specification for Additive Manufacturing File Format (AMF) Version 1.1.
ISO/ASTM 52921, 2013, Standard Terminology for Additive Manufacturing-Coordinate Systems and Test Methodologies.
ISO 17296-1, 2014, Additive Manufacturing—General—Part 1: Terminology.
ISO 17296-4, 2014, Additive Manufacturing—General Principles—Part 4: Overview of Data Processing Technologies, ASTM Fact Sheet.
ISO 17296-3, 2014, Additive Manufacturing—General Principles—Part 3: Main Characteristics and Corresponding Test Methods.
ISO 17296-2, 2015, Additive Manufacturing—General Principles—Part 2: Overview of Process Categories and Feedstock.
Kruth, J. P. , 1991, “ Material Incress Manufacturing by Rapid Prototyping Techniques,” CIRP Ann., 40(2), pp. 1603–1615. [CrossRef]
Lart, G. , 1992, “ Comparison of Rapid Prototyping Systems,” First European Conference on Rapid Prototyping, University of Nottingham, Nottingham, UK, pp. 243–254.
Ippolito, N. R. , Iuliano, L. , and de Filippi, A. , 1994, “ A New User Part for Performance Evaluation of Rapid Prototyping Systems,” Third European Conference on Rapid Prototyping and Manufacturing, University of Nottingham, Nottingham, UK, pp. 327–339.
Juster, N. P. , and Childs, T. H. C. , 1994, “ Linear and Geometric Accuracies From Layer Manufacturing,” CIRP Ann., 43(1), pp. 163–166. [CrossRef]
Juster, N. P. , and Childs, T. H. C. , 1994, “ A Comparison of Rapid Prototyping Processes,” Third European Conference on Rapid Prototyping and Manufacturing, University of Nottingham, Nottingham, UK, pp. 35–52.
Shellabear, M. , 1999, “ Benchmarking Study of Accuracy and Surface Quality in RP Models,” RAPTEC, Task 4.2, Report No. 2.
Mahesh, M. , Wong, Y. S. , Fuh, Y. H. , and Loh, H. T. , 2004, “ Benchmarking for Comparative Evaluation of RP Systems and Processes,” Rapid Prototyping J., 10(2), pp. 123–135. [CrossRef]
Sercombe, T. B. , and Hopkinson, N. , 2006, “ Process Shrinkage and Accuracy During Indirect Laser Sintering of Aluminum,” Adv. Eng. Mater., 8(4), pp. 260–264. [CrossRef]
Fahad, M. , and Hopkinson, N. , 2012, “ A New Benchmarking Part for Evaluating the Accuracy and Repeatability of Additive Manufacturing (AM) Processes,” 2nd International Conference on Mechanical, Production and Automobile Engineering (ICMPAE 2012), Singapore, April 28–29, pp. 234–238.
Lanzotti, A. , Martorelli, M. , and Staiano, G. , 2015, “ Understanding Process Parameter Effects of RepRap Open-Source Three-Dimensional Printers Through a Design of Experiments Approach,” ASME J. Manuf. Sci. Eng., 137(1), p. 011017. [CrossRef]
Shah, J. , and Mantyla, M. , 1995, Parametric and Feature-Based CAD/CAM: Concepts, Techniques, and Applications, Wiley-Inter-Science, New York.
Chen, Y. M. , Wen, C.-C. , and Ho, C. , 2003, “ Extraction of Geometric Characteristics for Manufacturability Assessment,” Rob. Comput. Integr. Manuf., 19(4), pp. 371–385. [CrossRef]
Gayretli, A. , and Abdalla, H. S. , 1999, “ A Feature-Based Prototype System for the Evaluation and Optimisation of Manufacturing Processes,” Comput. Ind. Eng., 37(1–2), pp. 481–484. [CrossRef]
Ip, C. Y. , and Regli, W. C. , 2006, “ A 3D Object Classifier for Discriminating Manufacturing Processes,” Comput. Graph., 30(6), pp. 903–916. [CrossRef]
Zhang, Y. , and Bernard, A. , 2014, “ Using AM Feature and Multi-Attribute Decision Making to Orientate Part in Additive Manufacturing,” High Value Manufacturing: Advanced Research in Virtual and Rapid Prototyping, P. J. da Silva Bártolo , A. C. Soares de Lemos , A. M. H. Pereira , A. J. dos Santos Mateus , C. Ramos , C. dos Santos , D. Oliveira , E. Pinto , F. Craveiro , H. M. Coelho da Rocha Terreiro Galha Bártolo , H. de Amorim Almeia , I. Sousa , J. M. Matias , L. Durão , M. Gaspar , N. M. F. Alves , P. Carreira , T. Ferreira , and T. Marques , eds., Taylor & Francis Group, London.
Rosen, D. W. , 2007, “ Computer-Aided Design for Additive Manufacturing of Cellular Structures,” CAD Appl., 4(5), pp. 585–594.
Qian, X. , and Dutta, D. , 2001, “ Feature Based Fabrication in Layered Manufacturing,” ASME J. Mech. Des., 123(3), pp. 337–345. [CrossRef]
Moroni, G. , Syam, W. P. , and Petrò, S. , 2014, “ Towards Early Estimation of Part Accuracy in Additive Manufacturing,” Procedia CIRP, 24th CIRP Design Conference, Vol. 21, pp. 300–305.
Moroni, G. , Syam, W. P. , and Petrò, S. , 2015, “ Functionality-Based Part Orientation for Additive Manufacturing,” Procedia CIRP, 25th CIRP Design Conference, pp. 1–7.
Besl, P. J. , and McKay, N. D. , 1992, “ A Method for Registration of 3-D Shapes,” IEEE Trans. Pattern Anal. Mach. Intell., 14(2), pp. 239–256. [CrossRef]
Pottmann, H. , Leopoldseder, S. , and Hofer, M. , 2002, “ Simultaneous Registration of Multiple Views of a 3D Object,” PCV’02, Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXIV, Part 3A, Commission III, pp. 265–270.
Campbell, R. I. , Martorelli, M. , and Lee, H. S. , 2002, “ Surface Roughness Visualisation for Rapid Prototyping Models,” Comput. Aided Des., 34(10), pp. 717–725. [CrossRef]

Figures

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Fig. 1

The open-source RepRap Prusa Mendel I2 used in this case study

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Fig. 2

Five geometric features selected in the benchmarking part

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Fig. 3

Benchmarking part RE acquisition by D700 Laser Scanner Fig. 4 Tensile test specimen

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Fig. 4

Common subset of scan data extracted for each geometric feature

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Fig. 5

Three-dimensional colored maps of deviations for the first replicate

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Fig. 6

Box-plots of the RMSE grouped by geometric features

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Fig. 7

Main effect plots obtained for each geometric feature for RMSE

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Fig. 8

Main (Lt) and interaction (Lt × Fr) effects for the cone

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Fig. 9

Main effects plot for RMSE average across all the geometric features

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Fig. 10

Interaction plot of the RMSE average across all the geometric features

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