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Maintenance Framework for Repairing Partially Damaged Parts Using 3D Printing

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Abstract

Additive manufacturing via 3D printing can enable the efficient and cost-effective replacement of damaged parts that can be produced at any manufacturing location and even when the parts are discontinued but their 3D CAD models are available. In addition, damaged portions of a part can be reconstructed by utilizing 3D printing. However, using a 3D printer requires a skilled operator with knowledge of this technology and other technical aspects. Hence, in this research, a user-friendly maintenance framework has proposed for any operator to repair partially damaged parts using 3D printing without requiring expert technical support. The framework includes a parts catalog with information necessary for 3D printing, a search module for automatically identifying damaged parts without prior knowledge about the part, and a shape comparison module for validation of the repaired part through damage detection and error measurement. Design and implementation of a maintenance support system based on the proposed framework are explained and the result of conducted experiment with a damaged ball from a valve to verify its performance is presented.

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References

  1. Bak, D. (2003). Rapid prototyping or rapid production? 3D printing processes move industry towards the latter. Assembly Automation, 23(4), 340–345.

    Article  Google Scholar 

  2. Ahn, D. G. (2011). Applications of laser assisted metal rapid tooling process to manufacture of molding and forming tools—State of the art. International Journal of Precision Engineering and Manufacturing, 12(5), 925–938.

    Article  Google Scholar 

  3. Ahn, D. G. (2016). Direct metal additive manufacturing processes and their sustainable applications for green technology: A review. International Journal of Precision Engineering and Manufacturing-Green Technology, 3(4), 381–395.

    Article  Google Scholar 

  4. Louis, M. J., Seymour, T., & Joyce, J. (2014). 3D opportunity for the department of defense: Additive manufacturing fires up. A Deloitte Series on Additive Manufacturing, Deloitte University Press.

  5. Kim, H., Cha, M., Kim, B. C., Kim, T., & Mun, D. (2018). Part library-based information retrieval and inspection framework to support part maintenance using 3D printing technology. Rapid Prototyping Journal. https://doi.org/10.1108/RPJ-06-2018-0139.

    Google Scholar 

  6. Ahn, D. G., Lee, H. J., Cho, J. R., & Guk, D. S. (2016). Improvement of the wear resistance of hot forging dies using a locally selective deposition technology with transition layers. CIRP Annals, 65(1), 257–260.

    Article  Google Scholar 

  7. Hong, M. P., Kim, W. S., Sung, J. H., Kim, D. H., Bae, K. M., & Kim, Y. S. (2018). High-performance eco-friendly trimming die manufacturing using heterogeneous material additive manufacturing technologies. International Journal of Precision Engineering and Manufacturing-Green Technology, 5(1), 133–142.

    Article  Google Scholar 

  8. ASTM Committee F42 on Additive Manufacturing Technologies. Subcommittee F42.91. (2012). Standard terminology for additive manufacturing technologies. West Conshohocken: ASTM International.

    Google Scholar 

  9. Frazier, W. E. (2014). Metal additive manufacturing: A review. Journal of Materials Engineering and Performance, 23(6), 1917–1928.

    Article  Google Scholar 

  10. Kai, C. C., Jacob, G. G., & Mei, T. (1997). Interface between CAD and rapid prototyping systems. Part 1: A study of existing interfaces. The International Journal of Advanced Manufacturing Technology, 13(8), 566–570.

    Article  Google Scholar 

  11. ASTM Committee F42 on Additive Manufacturing Technologies. Subcommittee F42.04. (2016). Standard specification for additive manufacturing file format (AMF) version 1.2. West Conshohocken: ASTM International.

    Google Scholar 

  12. MF Consortium. (2016). 3D manufacturing format—Core specification and reference guide version 1.1. http://www.3mf.io/wp-content/uploads/2016/03/3MFcoreSpec_1.1.pdf. Last accessed on March 26, 2018.

  13. Hällgren, S., Pejryd, L., & Ekengren, J. (2016). 3D data export for additive manufacturing-improving geometric accuracy. Procedia CIRP, 50, 518–523.

    Article  Google Scholar 

  14. Jee, H. J., & Sachs, E. (2000). A visual simulation technique for 3D printing. Advances in Engineering Software, 31(2), 97–106.

    Article  Google Scholar 

  15. Jin, G. Q., Li, W. D., Tsai, C. F., & Wang, L. (2011). Adaptive tool-path generation of rapid prototyping for complex product models. Journal of Manufacturing Systems, 30(3), 154–164.

    Article  Google Scholar 

  16. Singh, P., & Dutta, D. (2001). Multi-direction slicing for layered manufacturing. Journal of Computing and Information Science in Engineering, 1(2), 129–142.

    Article  Google Scholar 

  17. Lee, K., & Jee, H. (2015). Slicing algorithms for multi-axis 3-D metal printing of overhangs. Journal of Mechanical Science and Technology, 29(12), 5139–5144.

    Article  Google Scholar 

  18. Lee, K., & Jee, H. (2017). Verification of build part and tool paths for metal 3-D printing process. Transactions of the Korean Society of Mechanical Engineers A, 41(2), 103–109.

    Google Scholar 

  19. Kwon, S., Kim, B. C., Hwang, H., Mun, D., & Han, S. (2016). Enhancement of equipment information sharing using three-dimensional computer-aided design simplification and digital catalog techniques in the plant industry. Concurrent Engineering, 24(3), 275–289.

    Article  Google Scholar 

  20. Pierra, G., Potier, J. C., & Sardet, E. (2003). From digital libraries to electronic catalogues for engineering and manufacturing. International Journal of Computer Applications in Technology, 18(1–4), 27–42.

    Article  Google Scholar 

  21. Kim, B. C., Teijgeler, H., Mun, D., & Han, S. (2011). Integration of distributed plant lifecycle data using ISO 15926 and Web services. Annals of Nuclear Energy, 38(11), 2309–2318.

    Article  Google Scholar 

  22. Kim, H., Cha, M., & Mun, D. (2017). Shape distribution-based retrieval of 3D CAD models at different levels of detail. Multimedia Tools and Applications, 76(14), 15867–15884.

    Article  Google Scholar 

  23. Tangelder, J. W., & Veltkamp, R. C. (2008). A survey of content based 3D shape retrieval methods. Multimedia Tools and Applications, 39(3), 441–471.

    Article  Google Scholar 

  24. Iyer, N., Jayanti, S., Lou, K., Kalyanaraman, Y., & Ramani, K. (2005). Three-dimensional shape searching: State-of-the-art review and future trends. Computer-Aided Design, 37(5), 509–530.

    Article  Google Scholar 

  25. Paquet, E., Rioux, M., Murching, A., Naveen, T., & Tabatabai, A. (2000). Description of shape information for 2-D and 3-D objects. Signal Processing: Image Communication, 16(1–2), 103–122.

    Google Scholar 

  26. Ramesh, M., Yip-Hoi, D., & Dutta, D. (2001). Feature based shape similarity measurement for retrieval of mechanical parts. Journal of Computing and Information Science in Engineering, 1(3), 245–256.

    Article  Google Scholar 

  27. El-Mehalawi, M., & Miller, R. A. (2003). A database system of mechanical components based on geometric and topological similarity. Part I: Representation. Computer-Aided Design, 35(1), 83–94.

    Article  Google Scholar 

  28. Horn, B. K. P. (1984). Extended Gaussian images. Proceedings of the IEEE, 72(12), 1671–1686.

    Article  Google Scholar 

  29. Osada, R., Funkhouser, T., Chazelle, B., & Dobkin, D. (2002). Shape distributions. ACM Transactions on Graphics (TOG), 21(4), 807–832.

    Article  MathSciNet  MATH  Google Scholar 

  30. Ohbuchi, R., Minamitani, T., & Takei, T. (2005). Shape-similarity search of 3D models by using enhanced shape functions. International Journal of Computer Applications in Technology, 23(2–4), 70–85.

    Article  Google Scholar 

  31. Mun, D., & Ramani, K. (2011). Knowledge-based part similarity measurement utilizing ontology and multi-criteria decision making technique. Advanced Engineering Informatics, 25(2), 119–130.

    Article  Google Scholar 

  32. Jayanti, S., Kalyanaraman, Y., Iyer, N., & Ramani, K. (2006). Developing an engineering shape benchmark for CAD models. Computer-Aided Design, 38(9), 939–953.

    Article  Google Scholar 

  33. Su, H., Maji, S., Kalogerakis, E., & Learned-Miller, E. (2015). Multi-view convolutional neural networks for 3D shape recognition. In Proceedings of the 2015 IEEE international conference on computer vision (pp. 945–953).

  34. Kanezaki, A., Matsushita, Y., & Nishida, Y. (2018). RotationNet: Joint object categorization and pose estimation using multiviews from unsupervised viewpoints. arXiv preprint arXiv:1603.06208.

  35. Besl, P., & McKay, N. (1992). A method for registration of 3-D shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2), 239–256.

    Article  Google Scholar 

  36. Johnson, A., & Kang, S. (1997). Registration and integration of textured 3-D data. In Proceedings of the international conference on recent advances in 3-D digital imaging and modeling.

  37. Chen, Y., & Medioni, G. (1991). Object modeling by registration of multiple range images. In Proceedings of the IEEE conference on robotics and automation.

  38. Blais, G., & Levine, M. (1995). Registering multiview range data to create 3D computer objects. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(8), 820–824.

    Article  Google Scholar 

  39. Neugebauer, P. (1997). Geometrical cloning of 3D objects via simultaneous registration of multiple range images. In Proceedings of the international conference on shape modeling and applications.

  40. Kazhdan, M., Bolitho, M., & Hoppe, H. (2006). Poisson surface reconstruction. In Proceedings of the symposium on geometry processing 2006 (pp. 61–70).

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Acknowledgements

This study was supported by the Industry Core Technology Development Program (Project ID: 20000725) funded by the Ministry of Trade, Industry and Energy, by the Civil-Military Program (Project ID: CMP-16-01-KIST) funded by the National Research Council of Science and Technology of the Korean government, by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03028274), and by research funds for newly appointed professor of Chonbuk National University in 2018.

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Correspondence to Duhwan Mun.

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Kim, H., Cha, M., Kim, B.C. et al. Maintenance Framework for Repairing Partially Damaged Parts Using 3D Printing. Int. J. Precis. Eng. Manuf. 20, 1451–1464 (2019). https://doi.org/10.1007/s12541-019-00132-x

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