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Research Papers

Surface Topography of Additive Manufacturing Parts Using a Finite Difference Approach

[+] Author and Article Information
Saeed Jamiolahmadi

Department of Automotive, Mechanical and
Manufacturing Engineering,
Faculty of Engineering and Applied Science,
University of Ontario Institute of Technology,
2000 Simcoe Street North,
Oshawa, ON L1H 7K4, Canada
e-mail: Saeed.Jamiolahmadi@uoit.ca

Ahmad Barari

Mem. ASME
Department of Automotive, Mechanical and
Manufacturing Engineering,
Faculty of Engineering and Applied Science,
University of Ontario Institute of Technology,
2000 Simcoe Street North,
Oshawa, ON L1H 7K4, Canada
e-mail: Ahmad.Barari@uoit.ca

1Corresponding author.

Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING. Manuscript received April 14, 2014; final manuscript received September 12, 2014; published online October 24, 2014. Assoc. Editor: David L. Bourell.

J. Manuf. Sci. Eng 136(6), 061009 (Oct 24, 2014) (8 pages) Paper No: MANU-14-1178; doi: 10.1115/1.4028585 History: Received April 14, 2014; Revised September 12, 2014

Inspection of surface integrity in additive manufacturing (AM) parts essentially needs a detailed understanding of their actual surface topography. Today's optical surface topography and roughness measurement sensors only provide information of the discrete points measured from the manufactured surface and not a detailed reconstruction of the surface topography. This paper presents a finite difference approach for reconstruction of the surface topography using sample measured data points. The developed methodology can be used in the surface quality inspection of the additive manufactured parts, their surface texture modeling, surface integrity analysis, and in planning for the required postprocessing or down-stream surface finish processes suitable for them. The methodology is fully implemented, and variety of experiments is conducted. The results show that the developed methodology is successful to reconstructed surface topography of the AM parts.

Copyright © 2014 by ASME
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References

Barari, A., 2008, “Sources of Uncertainty in Coordinate Metrology of Automotive Body,” Proceedings of 2nd CIRP International Conference on Assembly Technologies and Systems (CATS 2008), Toronto, ON, Canada, Sept. 21–23, pp. 437–447.
Barari, A., 2010, “Cam-Based Inspection of Machined Surfaces,” 5th International Conference on Advances in Production Engineering—APE2010, Warsaw, Poland, June 17–19.
Barari, A., Elmaraghy, H. A., and Knopf, G. K., 2007, “Search-Guided Sampling to Reduce Uncertainty of Minimum Deviation Zone Estimation,” ASME J. Comput. Inf. Sci. Eng., 7(4), pp. 360–371. [CrossRef]
Barari, A., Elmaraghy, H. A., and Elmaraghy, W. H., 2009, “Design for Manufacturing of Sculptured Surfaces: A Computational Platform,” ASME J. Comput. Inf. Sci. Eng., 9(2), p. 021006. [CrossRef]
Barari, A., Elmaraghy, H. A., and Orban, P., 2009, “Nurbs Representation of Estimated Surfaces Resulting From Machining Errors,” Int. J. Comput. Integr. Manuf., 22(5), pp. 395–410. [CrossRef]
Barari, A., and Pop-Iliev, R., 2009, “Reducing Rigidity by Implementing Closed-Loop Engineering in Adaptable Design and Manufacturing Systems,” J. Manuf. Syst., 28(2–3), pp. 47–54. [CrossRef]
Elmaraghy, H. A., Barari, A., and Knopf, G. K., 2004, “Integrated Inspection and Machining for Maximum Conformance to Design Tolerances,” CIRP Ann. Manuf. Technol., 53(1), pp. 411–416. [CrossRef]
Reeves, P. E., and Cobbs, R. E.,1995, “Surface Deviation Modeling of LMT Processes—A Comparative Analysis,” Proceedings of the Fifth European Conference on Rapid Prototyping and Manufacturing, Helsinki, Finland, June, pp. 59–77.
Armillotta, A., Biggioggero, G. F., Carnevale, M., and Monno, M., 1999, “Optimization of Rapid Prototypes With Surface Finish Constraints: A Study on the FDM Technique,” 3rd International Conference on Management of Innovative Technologies, Piran, Slovenija, pp. 28–29.
Allen, S., and Dutta, D., 1994, “On the Computation of Part Orientation Using Support Structures in Layered Manufacturing,” Proceedings of Solid Freeform Fabrication Symposium, University of Texas at Austin, Austin, TX, June, pp. 259–269.
Cheng, W., Fuh, J. Y. H., Nee, A. Y. C., Wong, Y. S., Loh, H. T., and Miyazawa, T., 1995, “Multi-Objective Optimization of Part-Building Orientation in Stereo-Lithography,” Rapid Prototyping J., 1(4), pp. 12–23. [CrossRef]
McClurkin, J., and Rosen, D., 1997, “Computer Aided Build Style Decision Support for Stereolitho-Graphy,” Rapid Prototyping J., 4(1), pp. 4–13. [CrossRef]
Galantucci, L. M., Lavecchia, F., and Percoco, G., 2009, “Experimental Study Aiming to Enhance the Surface Finish of Fused Deposition Modeled Parts,” CIRP Ann. Manuf. Technol., 58(1), pp. 189–192. [CrossRef]
Espalin, D., Medina, F., and Wicker, R., 2009, “Vapor Smoothing, A Method for Improving FDM-Manufactured Part Surface Finish,” International Rep. of the W.M. Keck Center for 3D Innovation, University of Texas at El Paso, El Paso, TX.
Pandey, P. M., Reddy, N. V., and Dhande, S. G., 2003, “Improvement of Surface Finish by Staircase Machining in Fused Deposition Modeling,” J. Mater. Process. Technol., 132(1–3), pp. 323–331. [CrossRef]
Ahn, D., Kweon, J.-H., Kwon, S., Song, J., and Lee, S., 2009, “Representation of Surface Roughness in Fused Deposition Modeling,” J. Mater. Process. Technol., 209(15–16), pp. 5593–5600. [CrossRef]
Zhao, H., Zhang, G., Yin, Z., and Wu, L., 2013, “Effects of Interpass Idle Time on Thermal Stresses in Multipass Multilayer Weld-Based Rapid Prototyping,” ASME J. Manuf. Sci. Eng., 135(1), p. 011016. [CrossRef]
Paul, R., Anand, S., and Gerner, F., 2014, “Effect of Thermal Deformation on Part Errors in Metal Powder Based Additive Manufacturing Processes,” ASME J. Manuf. Sci. Eng., 136(3), p. 031009. [CrossRef]
Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., and Stuetzle, W., 1992, “Surface Reconstruction From Unorganized Points,” Proceedings of the 19th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH ‘92), New York, July, pp. 71–78.
Amenta, N., Choi, S., and Kolluri, R. K., 2001, “The Power Crust, Unions of Balls, and the Medial Axis Transform,” Comput. Geom. Theory Appl., 19(2–3), pp. 127–153. [CrossRef]
Axler, S., Bourdon, P., and Wade, R., 2001, Harmonic Function Theory, Springer, New York, Chap. 1. [CrossRef]
Kuran, Ü., 1972, “On the Mean-Value Property of Harmonic Functions,” Bull. Lond. Math. Soc., 4(3), pp. 311–312. [CrossRef]
Voruganti, H. K., Dasgupta, B., and Hommel, G., 2006, “A Novel Potential Field Based Domain Mapping Method,” Proceedings of 10th WSEAS Conference on Computers (ICCOMPP06), Athens, Greece, July 13–15, pp. 655–661.

Figures

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Fig. 1

u–v–e deviation space, detailed deviation zone representation

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Fig. 2

Additive manufactured part

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Fig. 3

Actual microscopic view of AM surface

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Fig. 4

Surface deviation space using 10% of initial points before iteration runs

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Fig. 5

Estimated surface topography using 10% of initial points after 50 iteration runs

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Fig. 6

Estimated surface topography using 10% of initial points after 100 iteration runs

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Fig. 7

Estimated surface topography using 10% of initial points after 500 iteration runs

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Fig. 8

3D surface reconstructed using 10% of initial points after 500 runs

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Fig. 9

Convergence of FDM while using 10% of initial points

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Fig. 10

Surface deviation space using 50% of initial points before iteration runs

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Fig. 11

Estimated surface topography using 50% of initial points after 50 iteration runs

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Fig. 12

Estimated surface topography using 50% of initial points after 100 iteration runs

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Fig. 13

Estimated surface topography using 50% of initial points after 500 iteration runs

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Fig. 14

3D surface reconstructed using 50% of initial points after 500 runs

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Fig. 15

Convergence of FDM while using 50% of initial points

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Fig. 16

Surface deviation space using 90% of initial points before iteration runs

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Fig. 17

Estimated surface topography using 90% of initial points after 50 iteration runs

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Fig. 18

Estimated surface topography using 90% of initial points after 100 iteration runs

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Fig. 19

Estimated surface topography using 90% of initial points after 500 iteration runs

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Fig. 20

3D surface reconstructed using 90% of initial points after 500 runs

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Fig. 21

Convergence of FDM while using 90% of initial points

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Fig. 22

Estimated roughness after 500 runs versus percentage of points used in FDM

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Fig. 23

Normalized difference of the estimated roughness and original roughness for percentage of points used in FDM

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