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Voxel-Based Geometry Reconstruction for Repairing and Remanufacturing of Metallic Components Via Additive Manufacturing

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Abstract

In the component repair process using additive manufacturing (AM) technique, reconstructing the repair volume is essential to generate the repair tool path and guide the AM system to deposit correct geometry on the worn parts. In this study, a novel repair volume reconstruction methodology based on voxel modeling was introduced. At first, the stereolithography (STL) models of the nominal and damaged components were acquired either from computer-aided design (CAD) modeling or through robot-aided 3D scanning. The pre-machining approach was introduced to guarantee the defective zone is accessible to repair tools. The damaged models were aligned with the nominal models by best-fitting their common convex-hull centroids. After that, these STL models were converted to voxel models using the Marching Cube algorithm. The accuracy of the transferred voxel models was investigated by comparing them with the exact geometry. Boolean operations algorithm based on constructive solid geometry was proposed to extract the repair volume by comparing the nominal and damaged voxel models. The Boolean operations can output both the repair volume that is missing from the damaged parts which should be restored by AM and the excess geometry which should be removed by subtractive machining. The proposed approach was implemented on three CAD models and three scanned models. The repair volumes for these damaged parts were successfully reconstructed. Three components were repaired via the directed energy deposition AM process. Finally, the bonding performance between the deposited layers and base parts was evaluated via tensile testing.

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The data that support the findings of this study are available on request.

References

  1. Lee, H., Lim, C. H. J., Low, M. J., Tham, N., Murukeshan, V. M., & Kim, Y.-J. (2017). Lasers in additive manufacturing: A review. International Journal of Precision Engineering and Manufacturing Technology, 4, 307–322. https://doi.org/10.1007/s40684-017-0037-7.

    Article  Google Scholar 

  2. Veiga, C., Loureiro, A. J. R., & Davim, J. P. (2012). Proprties and applications of titanium alloys. Reviews on Advanced Materials Science, 32, 133–148.

    Google Scholar 

  3. Nam, J., & Lee, S. W. (2018). Machinability of titanium alloy (Ti-6Al-4V) in environmentally-friendly micro-drilling process with nanofluid minimum quantity lubrication using nanodiamond particles. International Journal of Precision Engineering and Manufacturing Technology, 5, 29–35. https://doi.org/10.1007/s40684-018-0003-z.

    Article  Google Scholar 

  4. Aggarwal, V., Khangura, S. S., & Garg, R. K. (2015). Parametric modeling and optimization for wire electrical discharge machining of Inconel 718 using response surface methodology. International Journal of Advanced Manufacturing Technology, 79, 31–47. https://doi.org/10.1007/s00170-015-6797-8.

    Article  Google Scholar 

  5. Jia, Z., Liu, Y., Li, J., Liu, L.-J., & Li, H. (2015). Crack growth behavior at thermal fatigue of H13 tool steel processed by laser surface melting. International Journal of Fatigue, 78, 61–71. https://doi.org/10.1016/j.ijfatigue.2015.04.005.

    Article  Google Scholar 

  6. Khare, V., Sonkaria, S., Lee, G.-Y., Ahn, S.-H., & Chu, W.-S. (2017). From 3D to 4D printing—design, material and fabrication for multi-functional multi-materials. International Journal of Precision Engineering and Manufacturing Technology, 4, 291–299. https://doi.org/10.1007/s40684-017-0035-9.

    Article  Google Scholar 

  7. Dandekar, C. R., Shin, Y. C., & Barnes, J. (2010). Machinability improvement of titanium alloy (Ti–6Al–4V) via LAM and hybrid machining. International Journal of Machine Tools Manufacturing, 50, 174–182. https://doi.org/10.1016/j.ijmachtools.2009.10.013.

    Article  Google Scholar 

  8. Lee, C.-M., Woo, W.-S., & Roh, Y.-H. (2017). Remanufacturing: Trends and issues. International Journal of Precision Engineering and Manufacturing Technology, 4, 113–125. https://doi.org/10.1007/s40684-017-0015-0.

    Article  Google Scholar 

  9. Matsumoto, M., Yang, S., Martinsen, K., & Kainuma, Y. (2016). Trends and research challenges in remanufacturing. International Journal of Precision Engineering and Manufacturing Technology, 3, 129–142. https://doi.org/10.1007/s40684-016-0016-4.

    Article  Google Scholar 

  10. Chua, Z. Y., Ahn, I. H., & Moon, S. K. (2017). Process monitoring and inspection systems in metal additive manufacturing: Status and applications. International Journal of Precision Engineering and Manufacturing Technology, 4, 235–245. https://doi.org/10.1007/s40684-017-0029-7.

    Article  Google Scholar 

  11. 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 Technology, 3, 381–395. https://doi.org/10.1007/s40684-016-0048-9.

    Article  Google Scholar 

  12. Zhang, X., Li, W., Chen, X., Cui, W., & Liou, F. (2018). Evaluation of component repair using direct metal deposition from scanned data. International Journal of Advanced Manufacturing Technology, 95, 3335–3348. https://doi.org/10.1007/s00170-017-1455-y.

    Article  Google Scholar 

  13. Saboori, A., Aversa, A., Marchese, G., Biamino, S., Lombardi, M., & Fino, P. (2019). Application of directed energy deposition-based additive manufacturing in repair. Applied Science. https://doi.org/10.3390/app9163316.

    Article  Google Scholar 

  14. Park, K. T., Kang, Y. T., Yang, S. G., Zhao, W. B., Kang, Y.-S., Im, S. J., et al. (2020). Cyber physical energy system for saving energy of the dyeing process with industrial internet of things and manufacturing big data. International Journal of Precision Engineering and Manufacturing Technology, 7, 219–238. https://doi.org/10.1007/s40684-019-00084-7.

    Article  Google Scholar 

  15. Kang, H. S., Lee, J. Y., Choi, S., Kim, H., Park, J. H., Son, J. Y., et al. (2016). Smart manufacturing: Past research, present findings, and future directions. International Journal of Precision Engineering and Manufacturing Technology, 3, 111–128. https://doi.org/10.1007/s40684-016-0015-5.

    Article  Google Scholar 

  16. Bennett, J., Dudas, R., Cao, J., Ehmann, K., Hyatt, G. (2016). Control of heating and cooling for direct laser deposition repair of cast iron components. In 2016 international symposium flex automive, 2016 (pp. 229–236). https://doi.org/10.1109/ISFA.2016.7790166.

  17. Graf, B., Gumenyuk, A., & Rethmeier, M. (2012). Laser metal deposition as repair technology for stainless steel and titanium alloys. Physics Procedia, 39, 376–381. https://doi.org/10.1016/j.phpro.2012.10.051.

    Article  Google Scholar 

  18. Liu, Q., Wang, Y., Zheng, H., Tang, K., Li, H., & Gong, S. (2016). TC17 titanium alloy laser melting deposition repair process and properties. Optics and Laser Technology, 82, 1–9. https://doi.org/10.1016/j.optlastec.2016.02.013.

    Article  Google Scholar 

  19. Pinkerton, A. J., Wang, W., & Li, L. (2008). Component repair using laser direct metal deposition. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 222, 827–836. https://doi.org/10.1243/09544054JEM1008.

    Article  Google Scholar 

  20. Song, J., Deng, Q., Chen, C., Hu, D., & Li, Y. (2006). Rebuilding of metal components with laser cladding forming. Applied Surface Science, 252, 7934–7940. https://doi.org/10.1016/j.apsusc.2005.10.025.

    Article  Google Scholar 

  21. Zhang, X., Pan, T., Li, W., & Liou, F. (2019). Experimental characterization of a direct metal deposited cobalt-based alloy on tool steel for component repair. JOM Journal of the Minerals Metals and Materials Society, 71, 946–955. https://doi.org/10.1007/s11837-018-3221-5.

    Article  Google Scholar 

  22. Lin, X., Cao, Y., Wu, X., Yang, H., Chen, J., & Huang, W. (2012). Microstructure and mechanical properties of laser forming repaired 17-4PH stainless steel. Materials Science and Engineering A, 553, 80–88. https://doi.org/10.1016/j.msea.2012.05.095.

    Article  Google Scholar 

  23. Yilmaz, O., Gindy, N., & Gao, J. (2010). A repair and overhaul methodology for aeroengine components. Robotics and Computer Integrated-Manufacturing, 26, 190–201. https://doi.org/10.1016/j.rcim.2009.07.001.

    Article  Google Scholar 

  24. He, J., Li, L., Li, J. (2011). Research of key-technique on automatic repair system of plane blade welding. In 2011 international conference control automation system engineering, 2011 (pp. 1–4). https://doi.org/10.1109/ICCASE.2011.5997615.

  25. Zhang, X., Li, W., & Liou, F. (2018). Damage detection and reconstruction algorithm in repairing compressor blade by direct metal deposition. International Journal of Advanced Manufacturing Technology, 95, 2393–2404. https://doi.org/10.1007/s00170-017-1413-8.

    Article  Google Scholar 

  26. Wilson, J. M., Piya, C., Shin, Y. C., Zhao, F., & Ramani, K. (2014). Remanufacturing of turbine blades by laser direct deposition with its energy and environmental impact analysis. J Clean Prod, 80, 170–178. https://doi.org/10.1016/j.jclepro.2014.05.084.

    Article  Google Scholar 

  27. Piya, C., Wilson, J. M., Murugappan, S., Shin, Y., & Ramani, K. (2011). Virtual repair: Geometric reconstruction for remanufacturing gas turbine blades. Proceedings of ASME Design Engineering Technical Conferences, 9, 895–904. https://doi.org/10.1115/DETC2011-48652.

    Article  Google Scholar 

  28. Li, J., Yao, F., Liu, Y., Wu, Y. (2010). Reconstruction of broken blade geometry model based on reverse engineering. In 2010 third international conference on intelligent networks and intelligent systems (pp. 680–682). https://doi.org/10.1109/ICINIS.2010.16.

  29. Wang, Z., Liu, R., Sparks, T., Liu, H., & Liou, F. (2015). Stereo vision based hybrid manufacturing process for precision metal parts. Precision Engineering, 42, 1–5. https://doi.org/10.1016/j.precisioneng.2014.11.012.

    Article  Google Scholar 

  30. Feng, C., Liang, J., Gong, C., Pai, W., & Liu, S. (2018). Repair volume extraction method for damaged parts in remanufacturing repair. International Journal of Advanced Manufacturing Technology, 98, 1523–1536. https://doi.org/10.1007/s00170-018-2300-7.

    Article  Google Scholar 

  31. Zhang, X., Li, W., Adkison, K. M., & Liou, F. (2018). Damage reconstruction from tri-dexel data for laser-aided repairing of metallic components. International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-018-1830-3.

    Article  Google Scholar 

  32. Liu, R., Wang, Z., & Liou, F. (2017). Multifeature-fitting and shape-adaption algorithm for component repair. Journal of Manufacturing Science and Engineering, 140, 21003–21019.

    Article  Google Scholar 

  33. Foley. J. D., Van, F. D., Van Dam, A., Feiner, S. K., Hughes, J. F., Hughes, J., et al. (1996). Computer graphics: principles and practice. Addison-Wesley Prof (p. 12110).

  34. Zheng, J., Li, Z., & Chen, X. (2006). Worn area modeling for automating the repair of turbine blades. International Journal of Advanced Manufacturing Technology, 29, 1062–1067. https://doi.org/10.1007/s00170-003-1990-6.

    Article  Google Scholar 

  35. Dinda, S., Modi, D., Simpson, T. W., Tedia, S., Williams, C.B. (2017). Expediting build time, material, and cost estimation for material extrusion processes to enable mobile applications. https://doi.org/10.1115/DETC2017-68230.

  36. Loh, G. H., Pei, E., Harrison, D., & Monzón, M. D. (2018). An overview of functionally graded additive manufacturing. Additive Manufacturing, 23, 34–44. https://doi.org/10.1016/j.addma.2018.06.023.

    Article  Google Scholar 

  37. Rajon, D. A., & Bolch, W. E. (2003). Marching cube algorithm: review and trilinear interpolation adaptation for image-based dosimetric models. Computerized Medical Imaging and Graphics, 27, 411–435. https://doi.org/10.1016/S0895-6111(03)00032-6.

    Article  Google Scholar 

  38. Tomaz, B., Bogdan, V., Joze, B., & Igor, D. (2011). Speed and accuracy evaluation of additive manufacturing machines. Rapid Prototyping Journal, 17, 64–75. https://doi.org/10.1108/13552541111098644.

    Article  Google Scholar 

  39. Woo, W.-S., Kim, E.-J., Jeong, H.-I., & Lee, C.-M. (2020). Laser-assisted machining of Ti-6Al-4V fabricated by DED additive manufacturing. International Journal of Precision Engineering and Manufacturing Technology, 7, 559–572. https://doi.org/10.1007/s40684-020-00221-7.

    Article  Google Scholar 

  40. Kim, U. S., & Park, J. W. (2019). High-quality surface finishing of industrial three-dimensional metal additive manufacturing using electrochemical polishing. International Journal of Precision Engineering and Manufacturing Technology, 6, 11–21. https://doi.org/10.1007/s40684-019-00019-2.

    Article  Google Scholar 

  41. Tebaay, L. M., Hahn, M., & Tekkaya, A. E. (2020). Distortion and dilution behavior for laser metal deposition onto thin sheet metals. International Journal of Precision Engineering and Manufacturing Technology, 7, 625–634. https://doi.org/10.1007/s40684-020-00203-9.

    Article  Google Scholar 

  42. Grant, G., & Tabakoff, W. (1975). Erosion prediction in turbomachinery resulting from environmental solid particles. Journal of Aircraft, 12, 471–478. https://doi.org/10.2514/3.59826.

    Article  Google Scholar 

  43. Antony, K. C., Goward, G. W. (1988). Aircraft gas turbine blade and vane repair. Warrendale, PA, Metallurgical Society, 1988 (pp. 745–754).

  44. Yoon, H.-S., Lee, J.-Y., Kim, H.-S., Kim, M.-S., Kim, E.-S., Shin, Y.-J., et al. (2014). A comparison of energy consumption in bulk forming, subtractive, and additive processes: Review and case study. Int J Precis Eng Manuf Technol, 1, 261–279. https://doi.org/10.1007/s40684-014-0033-0.

    Article  Google Scholar 

  45. Zhao, W.-B., Jeong, J.-W., Noh, S., & Yee, J. T. (2015). Energy simulation framework integrated with green manufacturing-enabled PLM information model. International Journal of Precision Engineering and Manufacturing Technology, 2, 217–224. https://doi.org/10.1007/s40684-015-0025-8.

    Article  Google Scholar 

  46. Su, C., Jiang, X., Huo, G., Zou, Q., Zheng, Z., & Feng, H.-Y. (2020). Accurate model construction of deformed aero-engine blades for remanufacturing. International Journal of Advanced Manufacturing Technology, 106, 3239–3251. https://doi.org/10.1007/s00170-019-04688-w.

    Article  Google Scholar 

  47. Liu, R., Wang, Z., Zhang, Y., Sparks, T., Liou, F. (2016). A Smooth toolpath generation method for laser metal deposition. In Proceedings of 27th annual international solid freeform fabrication symposium Austin, Texax, USA (pp. 1038–1046).

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Acknowledgements

The support from NSF (Grants numbers CMMI-1547052, CMMI-1625736, EEC-1004839) and Center for Energy Technology and Strategy are appreciated. We also appreciate the financial support provided by the Center for Advanced Manufacturing Technologies and Intelligent Systems Center at the Missouri University of Science and Technology.

Funding

This project was funded by the U.S. National Science Foundation (Grants numbers CMMI-1547052, CMMI-1625736). We also appreciate the financial support provided by the Center for Advanced Manufacturing Technologies and Intelligent Systems Center at the Missouri S&T.

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  1. Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, Rolla, MO, 65409, USA

    Xinchang Zhang, Wenyuan Cui & Frank Liou

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  1. Xinchang Zhang
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Correspondence to Xinchang Zhang.

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Zhang, X., Cui, W. & Liou, F. Voxel-Based Geometry Reconstruction for Repairing and Remanufacturing of Metallic Components Via Additive Manufacturing. Int. J. of Precis. Eng. and Manuf.-Green Tech. 8, 1663–1686 (2021). https://doi.org/10.1007/s40684-020-00291-7

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