single-au.php

IJAT Vol.11 No.1 pp. 29-37
doi: 10.20965/ijat.2017.p0029
(2017)

Paper:

Views over last 60 days: 405

Evaluation of Additive Manufacturing Processes in Fabrication of Personalized Robot

Shushu Wang†, Rakshith Badarinath, El-Amine Lehtihet, and Vittaldas Prabhu

The Harold and Inge Marcus Department of Industrial and Manufacturing Engineering,
The Pennsylvania State University
University Park, PA 16802, USA

†Corresponding author

Received:
May 17, 2016
Accepted:
December 1, 2016
Published:
January 5, 2017
Keywords:
personalization, 3D printing, fused deposition modelling, material jetting, robot, dimensional and locational accuracy, tensile strength
Abstract

Customer participation in the design stage of creating personalized products is increasing. Additive manufacturing (AM) has become a popular enabler of personalization. In this study, we evaluate the fabrication of an open-source robot arm in terms of cost, build time, dimensional and locational accuracy, end-effector accuracy, and mechanical properties. The mechanical components of the table-top robot were fabricated using two different AM processes of fused deposition modeling (FDM) and material jetting (polymer jetting or PolyJet). A reduction of infill density by 50% in the FDM process slightly decreased the building time, material cost, and tensile strength, but induced a 95% reduction in yield strength. A simulation of the mechanical assembly using the CAD models for the robot and the expected tolerances of the components estimated the end-effector positioning accuracy as 0.01–0.22 mm. The 3D printed robot arm was redesigned and fabricated using the best evaluated process in this study.

Cite this article as:
S. Wang, R. Badarinath, E. Lehtihet, and V. Prabhu, “Evaluation of Additive Manufacturing Processes in Fabrication of Personalized Robot,” Int. J. Automation Technol., Vol.11, No.1, pp. 29-37, 2017.
Data files:
References
  1. [1] S. M. Davis, “From “future perfect”: Mass customizing,” Planning review, Vol.17, No.2, pp. 16-21, 1989.
  2. [2] A. M. Fiore, L. Seung-Eun, and G. Kunz, “Psychographic variables affecting willingness to use body-scanning,” J. of Business and Management, Vol.9, No.3, pp. 271, 2003.
  3. [3] F. Salvador , P. M. De Holan, and F. T. Piller, “Cracking the code of mass customization,” MIT Sloan management review, Vol.50, No.3, pp. 71, 2009.
  4. [4] K. Jiang, H. L. Lee, and R. W. Seifert, “Satisfying customer preferences via mass customization and mass production,” IIE Trans., Vol.38, No.1, pp. 25-38, 2006.
  5. [5] A. M. Kaplan and M. Haenlein, “Toward a parsimonious definition of traditional and electronic mass customization,” J. of product innovation management, Vol.23, No.2, pp. 168-182, 2006.
  6. [6] F. Salvador, P. M. De Holan, and F. T. Piller, “Cracking the code of mass customization,” MIT Sloan management review, Vol.50, No.3, pp. 71, 2009.
  7. [7] P. McIntosh, “White privilege and male privilege,” The Teacher in American Society: A Critical Anthology, p. 121, 2010.
  8. [8] A. Kumar, “Mass customization: manufacturing issues and taxonomic analyses.” Int. J. of Flexible Manufacturing Systems, Vol.19, No.4, pp. 625-629, 2007.
  9. [9] A. T. Sidambe, “Biocompatibility of advanced manufactured titanium implants – A review,” Materials, Vol.7, No.12, pp. 8168-8188, 2014.
  10. [10] http://www.stratasys.com/ [accessed Mar. 15, 2016]
  11. [11] U. I. Chung and Y. Tei, “Manufacturing of artificial bones using 3D inkjet printing technology,” Int. J. of Automation Technology, Vol.3, No.5, pp. 509-513, 2009.
  12. [12] S. H. Ahn, M. Montero, D. Odell, S. Roundy, and P. K. Wright, “Anisotropic material properties of fused deposition modeling ABS,” Rapid Prototyping J., Vol.8, No.4, pp. 248-257, 2002.
  13. [13] I. Ainsworth, M. Ristic, and D. Brujic, “CAD-based measurement path planning for free-form shapes using contact probes,” The Int. J. of Advanced Manufacturing Technology, Vol.16, No.1, pp. 23-31, 2000.
  14. [14] M. Mahesh, Y. S. Wong, J. Y. H. Fuh, and H. T. Loh, “Benchmarking for comparative evaluation of RP systems and processes,” Rapid Prototyping J., Vol.10, No.2, pp. 123-135, 2004.
  15. [15] O. M. F. Marwah, S. Sharif, and M. Ibrahim, “Direct Fabrication of IC Sacrificial Patterns via Rapid Prototyping Approaches,” Int. J. of Automation Technology, Vol.6, No.5, pp. 570-575, 2012.
  16. [16] G. D. Kim and J. H. Sung, “Bench mark test on rapid prototyping processes and machines for functional prototypes,” J. of the Korean Society for Precision Engineering, Vol.23, No.6, pp. 187-195, 2006.
  17. [17] G. D. Kim and Y. T. Oh, “A benchmark study on rapid prototyping processes and machines: quantitative comparisons of mechanical properties, accuracy, roughness, speed, and material cost,” Proc. of the Institution of Mechanical Engineers, Part B: J. of Engineering Manufacture, Vol.222, No.2, pp. 201-215, 2008.
  18. [18] L. Baich, G. Manogharan, and H. Marie, “Study of infill print design on production cost-time of 3D printed ABS parts,” Int. J. of Rapid Manufacturing, Vol.5, No.3-4, pp. 308-319, 2015.
  19. [19] http://my3dmatter.com/influence-infill-layer-height-pattern/ [accessed Mar. 15, 2016]
  20. [20] P. Corke, “Robotics, vision and control: fundamental algorithms in MATLAB,” Springer, Vol.73, 2011.
  21. [21] G. W. Melenka, J. S. Schofield, M. R. Dawson, and J. P. Carey, “Evaluation of dimensional accuracy and material properties of the MakerBot 3D desktop printer,” Rapid Prototyping J., Vol.21, No.5, pp. 618-627, 2015.
  22. [22] http://www.stratasys.com/˜/media/Main/Files/SDS/Rigid-Opaque-Materials/SDS-Objet-VeroBlue-RGD840-US.pdf [accessed Mar. 15, 2016]
  23. [23] S, Wang, R. Badarinath, V. V. Prabhu, E. A. Lehtihet, “Evaluation of additive manufacturing processes in fabrication of a personalized robot,” Paper presented at the Advances in Production Management Systems, APMS International Conference 2016, Brazil, South America, September, 2016.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Mar. 19, 2019