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In situ monitoring of direct energy deposition via structured light system and its application in remanufacturing industry

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Abstract

The direct energy deposition (DED) process utilizes laser energy to melt metal powders and deposit them on the substrate layer to manufacture complex metal parts. This study was applied as a remanufacturing and repair process to fix used parts, which reduced unnecessary waste in the manufacturing industry. However, there could be defects generated during the repair, such as porosity or bumpy morphological defects. Traditionally the operator would use a design of experiment (DOE) or simulation method to understand the printing parameters’ influence on the printed part. There are several influential factors: laser power, scanning speed, powder feeding rate, and standoff distance. Each DED machine has a different setup in practice, which results in some uncertainties for the printing results. For example, the nozzle diameter and laser type could be varied in different DED machines. Thus, it was hypothesized that a repair could be more effective if the printing process could be monitored in real time. In this study, a structured light system (SLS) was used to capture the printing process’s layer-wise information. The SLS system is capable of performing 3D surface scanning with a high resolution of 10 μm. It can provide the information to determine how much material needs to be deposited and monitor the layer-wide surface topography for each layer in real-time. Once a defect was found in situ, the DED machine (hybrid machine) would change the tool and remove the flawed layer. After the repair, the nondestructive approach computed tomography (CT) was applied to examine its interior features. In this research, a DED machine using 316L stainless steel was used to perform the repairing process to demonstrate its effectiveness. The lab-built SLS system was used to capture each layer’s information, and CT data was provided for the quality evaluation. The novel manufacturing approach could improve the DED repair quality, reduce the repair time, and promote repair automation. In the future, it has a great potential to be used in the manufacturing industry to repair used parts and avoid the extra cost involved in buying a new part.

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References

  1. Vartanian K, McDonald T (2016) Accelerating industrial adoption of metal additive manufacturing technology. Jom 68(3):806–810

    Article  Google Scholar 

  2. Ahn DG (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 

  3. Wilson JM, Piya C, Shin YC, 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

    Article  Google Scholar 

  4. Graf B, Gumenyuk A, Rethmeier M (2012) Laser metal deposition as repair technology for stainless steel and titanium alloys. Phys Procedia 39:376–381

    Article  Google Scholar 

  5. Leunda J, Soriano C, Sanz C, Navas VG (2011) Laser cladding of vanadium-carbide tool steels for die repair. Phys Procedia 12:345–352

    Article  Google Scholar 

  6. Onuike B, Bandyopadhyay A (2019) Additive manufacturing in repair: influence of processing parameters on properties of Inconel 718. Mater Lett 252:256–259

    Article  Google Scholar 

  7. Shuai C, Cheng Y, Yang Y, Peng S, Yang W, Qi F (2019) Laser additive manufacturing of Zn-2Al part for bone repair: formability, microstructure and properties. J Alloys Compd 798:606–615

    Article  Google Scholar 

  8. Petrat T, Brunner-Schwer C, Graf B, Rethmeier M (2019) Microstructure of Inconel 718 parts with constant mass energy input manufactured with direct energy deposition. Procedia Manufacturing 36:256–266

    Article  Google Scholar 

  9. Wang Z, Palmer TA, Beese AM (2016) Effect of processing parameters on microstructure and tensile properties of austenitic stainless steel 304L made by directed energy deposition additive manufacturing. Acta Mater 110:226–235

    Article  Google Scholar 

  10. Feenstra DR, Cruz V, Gao X, Molotnikov A, Birbilis N (2020) Effect of build height on the properties of large format stainless steel 316L fabricated via directed energy deposition. Additive Manufacturing 25:101205

    Article  Google Scholar 

  11. Woo W, Kim DK, Kingston EJ, Luzin V, Salvemini F, Hill MR (2019) Effect of interlayers and scanning strategies on through-thickness residual stress distributions in additive manufactured ferritic-austenitic steel structure. Mater Sci Eng A 744:618–629

    Article  Google Scholar 

  12. Shim DS, Baek GY, Lee EM (2017) Effect of substrate preheating by induction heater on direct energy deposition of AISI M4 powder. Mater Sci Eng A 682:550–562

    Article  Google Scholar 

  13. Chua ZY, Ahn IH, Moon SK (2017) Process monitoring and inspection systems in metal additive manufacturing: status and applications. International Journal of Precision Engineering and Manufacturing-Green Technology 4(2):235–245

    Article  Google Scholar 

  14. Elliot AM, Love LJ (2016) Operator burden in metal additive manufacturing. Solid Freeform Fabrication 1:1890–1899

    Google Scholar 

  15. Hofman JT, Pathiraj B, Van Dijk J, De Lange DF, Meijer J (2012) A camera based feedback control strategy for the laser cladding process. J Mater Process Technol 212(11):2455–2462

    Article  Google Scholar 

  16. Craeghs T, Clijsters S, Yasa E, Bechmann F, Berumen S, Kruth JP (2011) Determination of geometrical factors in layerwise laser melting using optical process monitoring. Opt Lasers Eng 49(12):1440–1446

    Article  Google Scholar 

  17. Farshidianfar MH, Khajepour A, Gerlich AP (2016) Effect of real-time cooling rate on microstructure in laser additive manufacturing. J Mater Process Technol 231:468–478

    Article  Google Scholar 

  18. Bandyopadhyay A, Traxel KD (2018) Invited review article: metal-additive manufacturing—Modeling strategies for application-optimized designs. Additive manufacturing 22:758–774

    Article  Google Scholar 

  19. Yang Q, Zhang P, Cheng L, Min Z, Chyu M, To AC (2016) Finite element modeling and validation of thermomechanical behavior of Ti-6Al-4V in directed energy deposition additive manufacturing. Additive Manufacturing 12:169–177

    Article  Google Scholar 

  20. Ding Y, Warton J, Kovacevic R (2016) Development of sensing and control system for robotized laser-based direct metal addition system. Additive Manufacturing 10:24–35

    Article  Google Scholar 

  21. Lott P, Schleifenbaum H, Meiners W, Wissenbach K, Hinke C, Bültmann J (2011) Design of an optical system for the in situ process monitoring of selective laser melting (SLM). Phys Procedia 12:683–690

    Article  Google Scholar 

  22. Li B, Zhang S (2014) Structured light system calibration method with optimal fringe angle. Appl Opt 53(33):7942–7950

    Article  Google Scholar 

  23. Townsend A, Senin N, Blunt L, Leach RK, Taylor JS (2016) Surface texture metrology for metal additive manufacturing: a review. Precis Eng 46:34–47

    Article  Google Scholar 

  24. Zhang X, Zheng Y, Suresh V, Wang S, Li Q, Li B, Qin H (2020) Correlation approach for quality assurance of additive manufactured parts based on optical metrology. J Manuf Process 53:310–317

    Article  Google Scholar 

  25. Zheng Y, Zhang X, Wang S, Li Q, Qin H, Li B (2020) Similarity evaluation of topography measurement results by different optical metrology technologies for additive manufactured parts. Opt Lasers Eng 126:105920

    Article  Google Scholar 

  26. Suresh V, Zheng Y, Zhang X, Wang S, Qin H, Li Q, Li B (2020) Similarity evaluation of 3D topological measurement results using statistical methods. In Dimensional Optical Metrology and Inspection for Practical Applications IX 11397:113970A

    Google Scholar 

  27. Melugiri-Shankaramurthy B, Sargam Y, Zhang X, Sun W, Wang K, Qin H (2019) Evaluation of cement paste containing recycled stainless steel powder for sustainable additive manufacturing. Constr Build Mater 227:116696

    Article  Google Scholar 

  28. Polamaplly P, Cheng Y, Shi X, Manikandan K, Zhang X, Kremer GE, Qin H (2019) 3D printing and characterization of hydroxypropyl methylcellulose and methylcellulose for biodegradable support structures. Polymer 173:119–126

    Article  Google Scholar 

  29. Aggarangsi P, Beuth JL (2006) Localized preheating approaches for reducing residual stress in additive manufacturing. International Solid Freeform Fabrication Symposium

  30. Matthews M, Trapp J, Guss G, Rubenchik A (2018) Direct measurements of laser absorptivity during metal melt pool formation associated with powder bed fusion additive manufacturing processes. Journal of Laser Applications 30(3):032302

    Article  Google Scholar 

  31. Li B, Zhang S (2015) Flexible calibration method for microscopic structured light system using telecentric lens. Opt Express 23(20):25795–25803

    Article  Google Scholar 

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Availability of data and materials

The authors confirm that the data supporting the findings of this study are available within the article.

Funding

This paper is based upon the work supported by the US Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Advanced Manufacturing Office Award Number DE-EE0007897 and by the Exploratory Research Project grant from Department of Industrial and Manufacturing Systems Engineering (IMSE_ERP) at Iowa State University. Their supports are greatly appreciated.

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Authors and Affiliations

  1. Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, IA, 50011, USA

    Xiao Zhang, Weijun Shen, Xuepeng Jiang, Qing Li & Hantang Qin

  2. Mechanical Engineering Department, Iowa State University, Ames, IA, 50011, USA

    Weijun Shen, Vignesh Suresh, Li-Hsin Yeh & Beiwen Li

  3. Departmnet of Industrial and Systems Engineering, Rochester Institute of Technology, Rochester, NY, 14623, USA

    Jakob Hamilton & Iris V. Rivero

  4. Center for Nondestructive Evaluation, Iowa State University, Ames, IA, 50011, USA

    Zhan Zhang & Hantang Qin

Authors
  1. Xiao Zhang
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  8. Qing Li
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Contributions

Conceptualization: X.Z., I.R., B.L, and H.Q.

Methodology: X.Z., W.S., V.S., J. H., L-H.Y., X.J., Z.Z., X.J., and H.Q.

Software: X.Z., W.S., V.S., J. H., L-H.Y., and X.J.

Validation: X.Z., W.S., V.S., J. H., L-H.Y., X.J., and X.J.

Formal analysis: X.Z., W.S., V.S., J. H., L-H.Y., X.J., and X.J.

Investigation: X.Z., W.S., V.S., J. H., L-H.Y., X.J., and X.J.

Resources: X.Z., W.S., V.S., J. H., L-H.Y., and X.J.

Data curation: X.Z., W.S., V.S., J. H., L-H.Y., and X.J.

Writing—original draft preparation: X.Z., W.S., and X.J.

Writing—review and editing: X.J., Y.C., Z.Z., and H.Q.

Visualization: X.Z.

Supervision: H.Q.

Project administration: H.Q.

Funding acquisition: I.R., B.L., and H.Q.

All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Hantang Qin.

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Ethical approval

All procedures performed in studies, where applicable, were in accordance with the ethical standards of Iowa State University and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Consent to publish

The participant has consented to the submission of the research to the journal.

Competing interests

This report was prepared as an account of work sponsored by an agency of the United States Government.

Disclaimer

Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

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Zhang, X., Shen, W., Suresh, V. et al. In situ monitoring of direct energy deposition via structured light system and its application in remanufacturing industry. Int J Adv Manuf Technol 116, 959–974 (2021). https://doi.org/10.1007/s00170-021-07495-4

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  • DOI: https://doi.org/10.1007/s00170-021-07495-4

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