Skip to main content
Log in

Research and prospect of on-line monitoring technology for laser additive manufacturing

  • Critical Review
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

This paper mainly discusses the current research status and development trend of on-line monitoring technology for laser additive manufacturing. We have analyzed various on-line monitoring techniques for laser additive manufacturing based on visual imaging, temperature field, spectral analysis, and acoustic principles. Numerous analyses are performed on the monitored objects, the melt pool, including melt pool temperature and morphology dimensions, and the formed parts, including microstructure and properties. The analysis of on-line monitoring techniques for laser additive manufacturing is expected to find the research directions that meet future development trends.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25

Similar content being viewed by others

Data availability

TransparenT.

Code availability

Not applicable.

References

  1. Hoye N, Li HJ, Cuiuri D, Paradowska A (2014) Measurement of residual stresses in titanium aerospace components formed via additive manufacturing. Mater Sci Forum 777:124–129. https://doi.org/10.4028/www.scientific.net/MSF.777.124

    Article  Google Scholar 

  2. Salmi M, Paloheimo KS, Tuomi J, Wolff J, Mäkitie A (2013) Accuracy of medical models made by additive manufacturing (rapid manufacturing). J Cranio-Maxillo-Fac Surg 41:603–609. https://doi.org/10.1016/j.jcms.2012.11.041

    Article  Google Scholar 

  3. Campbell I, Bourell D, Gibson I (2012) Additive manufacturing: rapid prototyping comes of age. Rapid Prototyp J 18:255–258. https://doi.org/10.1108/13552541211231563

    Article  Google Scholar 

  4. Ngo TD, Kashani A, Imbalzano G, Nguyen KTQ, Hui D (2018) Additive manufacturing (3D printing):a review of materials, methods, applications and challenges. Compos B Eng 143:172–196. https://doi.org/10.1016/j.compositesb.2018.02.012

    Article  Google Scholar 

  5. Murr LE (2018) A metallographic review of 3D printing/additive manufacturing of metal and alloy products and components. Metallogr Microstruct Anal 7:103–132. https://doi.org/10.1007/s13632-018-0433-6

    Article  Google Scholar 

  6. Cao L, Chen SY, Wei MW, Guo Q, Liang J, Liu CS, Wang M (2019) Effect of laser energy density on defects behavior of direct laser depositing 24CrNiMo alloy steel. Opt Laser Technol 111:541–553. https://doi.org/10.1016/j.optlastec.2018.10.025

    Article  Google Scholar 

  7. Liu QC, Elambasseril J, Sun SJ, Leary M, Brandt M, Sharp PK (2014) The effect of manufacturing defects on the fatigue behaviour of Ti-6Al-4V specimens fabricated using selective laser melting. Adv Mat Res 891(892):1519–1524. https://doi.org/10.4028/www.scientific.net/AMR.891-892.1519

    Article  Google Scholar 

  8. Gong HJ, Rafi K, Gu HF, Ram GDJ, Starr T, Stucker B (2015) Influence of defects on mechanical properties of Ti-6Al-4V components produced by selective laser melting and electron beam melting. Mater Des 86:545–554. https://doi.org/10.1016/j.matdes.2015.07.147

    Article  Google Scholar 

  9. Xie RD, Li DC, Cui B, Zhang LZ, Gao F (2018) A defects detection method based on infrared scanning in laser metal deposition process. Rapid Prototyp J 24:945–954. https://doi.org/10.1108/RPJ-04-2017-0053

    Article  Google Scholar 

  10. Liu WW, Saleheen KM, Tang ZJ, Wang H, Al-Hammadi G, Abdelrahman A, Zhao YX, Hua SG, Wang FT (2021) Review on scanning pattern evaluation in laser-based additive manufacturing. Opt Eng 60:070901. https://doi.org/10.1117/1.OE.60.7.070901

    Article  Google Scholar 

  11. Heralić A, Christiansson AK, Ottosson M, Lennartson B (2010) Increased stability in laser metal wire deposition through feedback from optical measurements. Opt Lasers Eng 48:478–485. https://doi.org/10.1016/j.optlaseng.2009.08.012

    Article  Google Scholar 

  12. Hofman JT, Pathiraj B, Dijk J, Lange DF, Meijer J (2012) A camera based feedback control strategy for the laser cladding process. J Mater Process Technol 212:2455–2462. https://doi.org/10.1016/j.jmatprotec.2012.06.027

    Article  Google Scholar 

  13. Li JS, Vijayavel BS, Bhaskar D, Jyoti M (2012) Control of melt pool temperature and deposition height during direct metal deposition process. Int J Adv Manuf Technol 58:247–256. https://doi.org/10.1007/s00170-011-3395-2

    Article  Google Scholar 

  14. Arias JL, Montealegre MA, Vidal F, Rodríguez J, Mann S, Abels P, Motmans F Real-time laser cladding control with variable spot size. In: Laser 3D Manufacturing, San Francisco, CA, 2014. SPIE. https://doi.org/10.1117/12.2040058

  15. Kanko JA, Sibley AP, Fraser JM (2016) In situ morphology-based defect detection of selective laser melting through inline coherent imaging. J Mater Process Technol 231:488–500. https://doi.org/10.1016/j.jmatprotec.2015.12.024

    Article  Google Scholar 

  16. Tang L, Landers RG (2011) Layer-to-layer height control for laser metal deposition process. J Manuf Sci Eng 133:021009. https://doi.org/10.1115/1.4003691

    Article  Google Scholar 

  17. Barua S, Liou F, Newkirk J, Sparks T (2014) Vision-based defect detection in laser metal deposition process. Rapid Prototyp J 20:77–85. https://doi.org/10.1108/RPJ-04-2012-0036

    Article  Google Scholar 

  18. Tan H, Chen J, Lin X, Zhang FY, Huang WD (2008) Research on molten pool temperature in the process of laser rapid forming. J Mater Process Technol 198:454–462. https://doi.org/10.1016/j.jmatprotec.2007.06.090

    Article  Google Scholar 

  19. Hu YP, Chen CW, Mukherjee K (2000) Measurement of temperature distributions during laser cladding process. J Laser Appl 12:126–130. https://doi.org/10.2351/1.521921

    Article  Google Scholar 

  20. Lin J, Steen WM (1998) An in-process method for the inverse estimation of the powder catchment efficiency during laser cladding. Opt Laser Technol 30:77–84. https://doi.org/10.1016/S0030-3992(98)00007-3

    Article  Google Scholar 

  21. Li L, Steen WM, Hibberd RD, Brookfield DJ In-process clad quality monitoring using optical method. In: Laser Assisted Processing, The Hague, Netherlands, 1990. SPIE. https://doi.org/10.1117/12.20624

  22. Song LJ, Mazumder J (2010) Feedback control of melt pool temperature during laser cladding process. IEEE Trans Control Syst Technol 19:1349–1356. https://doi.org/10.1109/TCST.2010.2093901

    Article  Google Scholar 

  23. Pavlov M, Novichenko D, Doubenskaia (2011) Optical diagnostics of deposition of metal matrix composites by laser cladding. Phys Procedia 12:674–682. https://doi.org/10.1016/j.phpro.2011.03.084

    Article  Google Scholar 

  24. Hu D, Kovacevic R (2003) Modelling and measuring the thermal behaviour of the molten pool in closed-loop controlled laser-based additive manufacturing. Proc Instn Mech Engrs Part B: J Engineering Manufacture 217:441–452. https://doi.org/10.1243/095440503321628125

    Article  Google Scholar 

  25. Hu DM, Kovacevic R (2003) Sensing, modeling and control for laser-based additive manufacturing. Int J Mach Tool Manufact 43:51–60. https://doi.org/10.1016/S0890-6955(02)00163-3

    Article  Google Scholar 

  26. Scharun M, Fricke-Begemann C, Noll R (2013) Laser-induced breakdown spectroscopy with multi-kHz fibre laser for mobile metal analysis tasks-a comparison of different analysis methods and with a mobile spark-discharge optical emission spectroscopy apparatus. Spectrochim Acta Part B 87:198–207. https://doi.org/10.1016/j.sab.2013.05.007

    Article  Google Scholar 

  27. Abdellatif G, Imam H (2002) A study of the laser plasma parameters at different laser wavelengths. Spectrochim Acta Part B 57:1155–1165. https://doi.org/10.1016/S0584-8547(02)00057-5

    Article  Google Scholar 

  28. Barnett C, Cahoon E, Almirall JR (2008) Wavelength dependence on the elemental analysis of glass by laser induced breakdown spectroscopy. Spectrochim Acta Part B 63:1016–1023. https://doi.org/10.1016/j.sab.2008.07.002

    Article  Google Scholar 

  29. Fornarini L, Spizzichino V, Colao F, Fantoni R, Lazic V (2006) Influence of laser wavelength on LIBS diagnostics applied to the analysis of ancient bronzes. Anal Bioanal Chem 385:272–280. https://doi.org/10.1007/s00216-006-0300-1

    Article  Google Scholar 

  30. Lu QY, Wong CH (2018) Additive manufacturing process monitoring and control by non-destructive testing techniques: challenges and in-process monitoring. Virtual Phys Prototy 13:39–48. https://doi.org/10.1080/17452759.2017.1351201

    Article  Google Scholar 

  31. Shin J, Mazumder J (2018) Composition monitoring using plasma diagnostics during direct metal deposition (DMD) process. Opt Laser Technol 106:40–46. https://doi.org/10.1016/j.optlastec.2018.03.020

    Article  Google Scholar 

  32. Plotnikov Y, Henkel D, Burdick J, French A, Sions J, Bourne K (2019) Infrared-assisted acoustic emission process monitoring for additive manufacturing. In: AIP Conference Proceedings, vol. 2102, no. May. https://doi.org/10.1063/1.5099710

  33. Lee YS, Kirka MM, Ferguson J, Paquit VC (2020) Correlations of cracking with scan strategy and build geometry in electron beam powder bed additive manufacturing. Addit Manuf 32:101031. https://doi.org/10.1016/j.addma.2019.101031

    Article  Google Scholar 

  34. Gaja H, Liou F (2017) Defects monitoring of laser metal deposition using acoustic emission sensor. Int J Adv Manuf Technol 90:561–574. https://doi.org/10.1007/s00170-016-9366-x

    Article  Google Scholar 

  35. Kouprianoff D, Luwes N, Newby E, Yadroitsava I, Yadroitsev I (2017) On-line monitoring of laser powder bed fusion by acoustic emission: acoustic emission for inspection of single tracks under different powder layer thickness. In: 2017 Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA-RobMech), https://doi.org/10.1109/RoboMech.2017.8261148

  36. Shevchik SA, Kenel C, Leinenbach C, Wasmer K (2018) Acoustic emission for in-situ quality monitoring in additive manufacturing using spectral convolutional neural networks. Addit Manuf 21:598–604. https://doi.org/10.1016/j.addma.2017.11.012

    Article  Google Scholar 

  37. Cerniglia D, Scafidi M, Pantano A, Rudlin J (2015) Inspection of additive manufactured layered components. Ultrasonics 62:292–298. https://doi.org/10.1016/j.ultras.2015.06.001

    Article  Google Scholar 

  38. Arısoy YM, Criales LE, Özel T (2019) Modeling and simulation of thermal field and solidification in laser powder bed fusion of nickel alloy IN625. Opt Laser Technol 109:278–292. https://doi.org/10.1016/j.optlastec.2018.08.016

    Article  Google Scholar 

  39. Yin J, Peng GY, Chen CP, Yang JJ, Zhu HH, Ke LD, Wang ZM, Wang DZ, Ma MM, Wang GQ, Zeng XY (2018) Thermal behavior and grain growth orientation during selective laser melting of Ti-6Al-4V alloy. J Mater Process Technol 260:57–65. https://doi.org/10.1016/j.jmatprotec.2018.04.035

    Article  Google Scholar 

  40. Schänzel M, Shakirov D, Ilin A, Ploshikhin V (2019) Coupled thermo-mechanical process simulation method for selective laser melting considering phase transformation steels. Comput Math Appl 78:2230–2246. https://doi.org/10.1016/j.camwa.2019.01.019

    Article  MathSciNet  MATH  Google Scholar 

  41. Panda BK, Sahoo S (2019) Thermo-mechanical modeling and validation of stress field during laser powder bed fusion of AlSi10Mg built part. Results Phys 12:1372–1381. https://doi.org/10.1016/j.rinp.2019.01.002

    Article  Google Scholar 

  42. Wei P, Wei ZY, Chen Z, He YY, Du J (2017) Thermal behavior in single track during selective laser melting of AlSi10Mg powder. Appl Phys A 123:604. https://doi.org/10.1007/s00339-017-1194-9

    Article  Google Scholar 

  43. Tan H, Chen J, Zhang FY, Lin X, Huang WD (2010) Estimation of laser solid forming process based on temperature measurement. Opt Laser Technol 42:47–54. https://doi.org/10.1016/j.optlastec.2009.04.016

    Article  Google Scholar 

  44. Bi GJ, Gasser A, Wissenbach K, Drenker A, Poprawe R (2006) Characterization of the process control for the direct laser metallic powder deposition. Surf Coat Technol 201:2676–2683. https://doi.org/10.1016/j.surfcoat.2006.05.006

    Article  Google Scholar 

  45. Tang L, Landers RG (2010) Melt pool temperature control for laser metal deposition processes-part II: layer-to-layer temperature control. J Manuf Sci Eng 132:011011. https://doi.org/10.1115/1.4000883

    Article  Google Scholar 

  46. Salehi D, Brandt M (2006) Melt pool temperature control using LabVIEW in Nd:YAG laser blown powder cladding process. Int J Adv Manuf Technol 29:273–278. https://doi.org/10.1007/s00170-005-2514-3

    Article  Google Scholar 

  47. Devesse W, Baere DD, Hinderdael M, Guillaume P (2016) Hardware-in-the-loop control of additive manufacturing processes using temperature feedback. J Laser Appl 28:022302. https://doi.org/10.2351/1.4943911

    Article  Google Scholar 

  48. Song LJ, Singh VB, Dutta B, Mazumder J (2012) Control of melt pool temperature and deposition height during direct metal deposition process. Int J Adv Manuf Technol 58:247–256. https://doi.org/10.1007/s00170-011-3395-2

    Article  Google Scholar 

  49. Tang L, Landers RG (2010) Melt pool temperature control for laser metal deposition processes-part I: online temperature control. J Manuf Sci Eng 132:011010. https://doi.org/10.1115/1.4000882

    Article  Google Scholar 

  50. Asselin M, Toyserkani E, Iravani-Tabrizipour M, Khajepour A (2005) Development of trinocular CCD-based optical detector for real-time monitoring of laser cladding. IEEE ASME Int Conf Adv Intell Mechatron 3:1190–1196. https://doi.org/10.1109/ICMA.2005.1626722

    Article  Google Scholar 

  51. Song LJ, Wang FH, Li SM, Han X (2017) Phase congruency melt pool edge extraction for laser additive manufacturing. J Mater Process Technol 250:261–269. https://doi.org/10.1016/j.jmatprotec.2017.07.013

    Article  Google Scholar 

  52. Fathi A, Khajepour A, Durali M, Toyserkani E (2008) Geometry control of the deposited layer in a nonplanar laser cladding process using a variable structure controller. J Manuf Sci Eng 130:031003. https://doi.org/10.1115/1.2823085

    Article  Google Scholar 

  53. Zeinali M, Khajepour A (2010) Height control in laser cladding using adaptive sliding mode technique: theory and experiment. J Manuf Sci Eng 132:041016. https://doi.org/10.1115/1.4002023

    Article  Google Scholar 

  54. Moralejo S, Penaranda X, Nieto S, Barrios A, Arrizubieta I, Tabernero I, Figueras J (2017) A feedforward controller for tuning laser cladding melt pool geometry in real time. Int J Adv Manuf Technol 89:821–831. https://doi.org/10.1007/s00170-016-9138-7

    Article  Google Scholar 

  55. Yang Q (2019) Study of size detection and control of molten pool during laser cladding. Hefei University of Technology. Hefei, China. https://kns.cnki.net/kcms/detail/detail.aspx?FileName=1019218904.nh&DbName=CMFD2019

  56. Ocylok S, Alexeev E, Mann S, Weisheit A, Wissenbach K, Kelbassa I (2014) Correlation of melt pool geometry and process parameters during laser metal deposition by coaxial process monitoring. Phys Procedia 56:228–238. https://doi.org/10.1016/j.phpro.2014.08.167

    Article  Google Scholar 

  57. Tabernero I, Lamikiz A, Martínez S, Ukar E, López De Lacalle LN (2012) Geometric modelling of added layers by coaxial laser cladding. Phys Procedia 39:913–920. https://doi.org/10.1016/j.phpro.2012.10.116

    Article  Google Scholar 

  58. Ding YY, Warton J, Kovacevic R (2016) Development of sensing and control system for robotized laser-based direct metal addition system. Addit Manuf 10:24–35. https://doi.org/10.1016/j.addma.2016.01.002

    Article  Google Scholar 

  59. Qin LY, Xu LL, Yang G, Liu Q, Wang W (2018) Analysis and prediction of melt pool size in laser deposition manufacturing. Infrared Laser Eng 47:80–86. https://doi.org/10.3788/IRLA201847.1106009

    Article  Google Scholar 

  60. Mutabue T, Colin C, Malot T, Aubry P (2004) Influence of process monitoring devices on direct manufacturing by laser cladding for aeronautic components. In: International Congress on Applications of Lasers & Electro-Optics, vol. 2004, no. 1. https://doi.org/10.2351/1.5060184

  61. Bi GJ, Gasser A, Wissenbach K, Drenker A, Poprawe R (2006) Identification and qualification of temperature signal for monitoring and control in laser cladding. Opt Lasers Eng 44:1348–1359. https://doi.org/10.1016/j.optlaseng.2006.01.009

    Article  Google Scholar 

  62. Craeghs T, Bechmann F, Berumen S, Kruth JP (2010) Feedback control of layer wise laser melting using optical sensors. Phys Procedia 5:505–514. https://doi.org/10.1016/j.phpro.2010.08.078

    Article  Google Scholar 

  63. Miyagi M, Tsukamoto T, Kawanaka H (2014) Adaptive shape control of laser-deposited metal structures by adjusting weld pool size. J Laser Appl 26:032003. https://doi.org/10.2351/1.4869499

    Article  Google Scholar 

  64. Ciucci A, Corsi M, Palleschi V, Rastelli S, Salvetti A, Tognoni E (1999) New procedure for quantitative elemental analysis by laser-induced plasma spectroscopy. Appl Spectrosc 53:960–964. https://doi.org/10.1366/0003702991947612

    Article  Google Scholar 

  65. Zhu XQ, Xu T, Lin QY, Liang L, Niu GH, Lai HJ, Xu MJ, Wang X, Li H, Duan YX (2014) Advanced statistical analysis of laser-induced breakdown spectroscopy data to discriminate sedimentary rocks based on Czerny-Turner and Echelle spectrometers. Spectrochim Acta Part B 93:8–13. https://doi.org/10.1016/j.sab.2014.01.001

    Article  Google Scholar 

  66. Tognoni E, Cristoforetti G, Legnaioli S, Palleschi V (2010) Calibration-free laser-induced breakdown spectroscopy: state of the art. Spectrochim Acta Part B 65:1–14. https://doi.org/10.1016/j.sab.2009.11.006

    Article  Google Scholar 

  67. Herrera KK, Tognoni E, Omenetto N, Smitha BW, Winefordner JD (2009) Semi-quantitative analysis of metal alloys, brass and soil samples by calibration-free laser-induced breakdown spectroscopy: recent results and considerations. J Anal At Spectrom 24:413–425. https://doi.org/10.1039/B820493D

    Article  Google Scholar 

  68. Tognoni E, Cristoforetti G, Legnaioli S, Palleschi V, Salvetti A, Mueller M, Panne U, Gornushkin I (2007) A numerical study of expected accuracy and precision in calibration-free laser-induced breakdown spectroscopy in the assumption of ideal analytical plasma. Spectrochim Acta Part B 62:1287–1302. https://doi.org/10.1016/j.sab.2007.10.005

    Article  Google Scholar 

  69. Cabalín L, Romero D, García CC, Baena J, Laserna J (2002) Time-resolved laser-induced plasma spectrometry for determination of minor elements in steelmaking process samples. Anal Bioanal Chem 372:352–359. https://doi.org/10.1007/s00216-001-1121-x

    Article  Google Scholar 

  70. Andrade JM, Cristoforetti G, Legnaioli S, Lorenzetti G, Palleschi V, Shaltout AA (2010) Classical univariate calibration and partial least squares for quantitative analysis of brass samples by laser-induced breakdown spectroscopy. Spectrochim Acta Part B 65:658–663. https://doi.org/10.1016/j.sab.2010.04.008

    Article  Google Scholar 

  71. Andrea ED, Pagnotta S, Grifoni E, Lorenzetti G, Legnaioli S, Palleschi V, Lazzerini B (2014) An artificial neural network approach to laser-induced breakdown spectroscopy quantitative analysis. Spectrochim Acta Part B 99:52–58. https://doi.org/10.1016/j.sab.2014.06.012

    Article  Google Scholar 

  72. Ayyalasomayajula KK, Yu-Yueh F, Singh JP, McIntyre DL, Jain J (2012) Application of laser-induced breakdown spectroscopy for total carbon quantification in soil samples. Appl Opt 51:149–154. https://doi.org/10.1364/AO.51.00B149

    Article  Google Scholar 

  73. Sirven JB, Bousquet B, Canioni L, Sarger L (2006) Laser-induced breakdown spectroscopy of composite samples: comparison of advanced chemometrics methods. Anal Chem 78:1462–1469. https://doi.org/10.1021/ac051721p

    Article  Google Scholar 

  74. Ferreira EC, Milori DMBP, Ferreira EJ, Silva RMD, Martin-Neto L (2008) Artificial neural network for Cu quantitative determination in soil using a portable laser induced breakdown spectroscopy system. Spectrochim Acta Part B 63:1216–1220. https://doi.org/10.1016/j.sab.2008.08.016

    Article  Google Scholar 

  75. Lednev VN, Sdvizhenskii PA, Asyutin RD, Tretyakov RS, Grishin MY, Stavertiy AY, Pershin SM (2019) In situ multi-elemental analysis by laser induced breakdown spectroscopy in additive manufacturing. Addit Manuf 25:64–70. https://doi.org/10.1016/j.addma.2018.10.043

    Article  Google Scholar 

  76. Lednev VN, Sdvizhenskii PA, Asyutin RD, Tretyakov RS, Grishin MY, Stavertiy AY, Fedorov AN, Pershin SM (2019) In situ elemental analysis and failures detection during additive manufacturing process utilizing laser induced breakdown spectroscopy. Opt Express 27:4612–4628. https://doi.org/10.1364/OE.27.004612

    Article  Google Scholar 

  77. Nassar AR, Keist JS, Reutzel EW, Spurgeon TJ (2015) Intra-layer closed-loop control of build plan during directed energy additive manufacturing of Ti-6Al-4V. Addi Manuf 6:39–52. https://doi.org/10.1016/j.addma.2015.03.005

    Article  Google Scholar 

  78. Song LJ, Mazumder J (2012) Real time Cr measurement using optical emission spectroscopy during direct metal deposition process. IEEE Sensors J 12:958–964. https://doi.org/10.1109/JSEN.2011.2162316

    Article  Google Scholar 

  79. Song LJ, Huang WK, Han X, Mazumder J (2017) Real-time composition monitoring using support vector regression of laser-induced plasma for laser additive manufacturing. IEEE Trans Ind Electron 64:633–642. https://doi.org/10.1109/TIE.2016.2608318

    Article  Google Scholar 

  80. Song LJ, Wang CS, Mazumder J (2012) Identification of phase transformation using optical emission spectroscopy for direct metal deposition process. In: High Power Laser Mater Processing Laser Beam Delivery Diagnostics Applications, San Francisco, CA, SPIE. https://doi.org/10.1117/12.908264

  81. Malý M, Höller C, Skalon M, Meier B, Koutný D, Pichler R, Sommitsch C, Paloušek D (2019) Effect of process parameters and high-temperature preheating on residual stress and relative density of Ti6Al4V processed by selective laser melting. Materials 12:930. https://doi.org/10.3390/ma12060930

    Article  Google Scholar 

  82. Sato Y, Tsukamoto M, Shobu T, Yamashita Y, Yamagata S, Nishi T, Higashino R, Ohkubo T, Nakano H, Abe N (2018) Preheat effect on titanium plate fabricated by sputter-free selective laser melting in vacuum. Appl Phys A 124:288. https://doi.org/10.1007/s00339-018-1712-4

    Article  Google Scholar 

  83. Ali H, Ma L, Ghadbeigi H, Mumtaz K (2017) In-situ residual stress reduction, martensitic decomposition and mechanical properties enhancement through high temperature powder bed pre-heating of Selective Laser Melted Ti6Al4V. Mater Sci Eng A 695:211–220. https://doi.org/10.1016/j.msea.2017.04.033

    Article  Google Scholar 

  84. Ding CG, Cui X, Jiao JQ, Zhu P (2018) Effects of substrate preheating temperatures on the microstructure, properties, and residual stress of 12CrNi2 prepared by laser cladding deposition technique. Materials 11:2401. https://doi.org/10.3390/ma11122401

    Article  Google Scholar 

  85. Kempen K, Vrancken B, Buls S, Thijs L, Humbeeck JV, Kruth JP (2014) Selective laser melting of crack-free high density M2 high speed steel parts by baseplate preheating. J Manuf Sci Eng 136:061026. https://doi.org/10.1115/1.4028513

    Article  Google Scholar 

  86. Fallah V, Alimardani M, Corbin SF, Khajepour A (2010) Impact of localized surface preheating on the microstructure and crack formation in laser direct deposition of Stellite 1 on AISI 4340 steel. Appl Surf Sci 257:1716–1723. https://doi.org/10.1016/j.apsusc.2010.09.003

    Article  Google Scholar 

  87. Zhang P, Ma L, Yuan JP, Cai ZH (2011) Analysis of stress and strain fields of laser cladding process on ring circular orbit. J Shanghai Jiaotong Univ 16:296–301. https://doi.org/10.1007/s12204-011-1147-y

    Article  Google Scholar 

  88. Farahmand P, Kovacevic R (2014) An experimental-numerical investigation of heat distribution and stress field in single-and multi-track laser cladding by a high-power direct diode laser. Opt Laser Technol 63:154–168. https://doi.org/10.1016/j.optlastec.2014.04.016

    Article  Google Scholar 

  89. Qi H, Mazumder J (2006) Numerical simulation of heat transfer and fluid flow in coaxial laser cladding process for direct metal deposition. J Appl Phys 100:024903. https://doi.org/10.1063/1.2209807

    Article  Google Scholar 

  90. Zhao XR, Iyer A, Promoppatum P, Yao SC (2017) Numerical modeling of the thermal behavior and residual stress in the direct metal laser sintering process of titanium alloy products. Addit Manuf 14:126–136. https://doi.org/10.1016/j.addma.2016.10.005

    Article  Google Scholar 

  91. Moat RJ, Pinkerton AJ, Li L, Withers PJ, Preuss M (2011) Residual stresses in laser direct metal deposited Waspaloy. Mater Sci Eng A 528:2288–2298. https://doi.org/10.1016/j.msea.2010.12.010

    Article  Google Scholar 

  92. Pratt P, Felicelli SD, Wang L, Hubbard CR (2008) Residual stress measurement of laser-engineered net shaping AISI 410 thin plates using neutron diffraction. Metall Mater Trans A 39:3155–3163. https://doi.org/10.1007/s11661-008-9660-9

    Article  Google Scholar 

  93. De Oliveira U, Ocelík V, De Hosson JTM (2006) Residual stress analysis in Co-based laser clad layers by laboratory X-rays and synchrotron diffraction techniques. Surf Coat Technol 201:533–542. https://doi.org/10.1016/j.surfcoat.2005.12.011

    Article  Google Scholar 

  94. Andreas L, Robert P, Magnus HC, Craig B, Axel S, Almir H, Thomas B, Lars-Erik L (2016) Modeling and experimental measurement with synchrotron radiation of residual stresses in laser metal deposited Ti-6Al-4V. In: Proceedings of the 13th World Conference on Titanium, pp. 1279–1282. https://doi.org/10.1002/9781119296126.ch216

  95. Biegler M, Graf B, Rethmeier M (2018) In-situ distortions in LMD additive manufacturing walls can be measured with digital image correlation and predicted using numerical simulations. Addit Manuf 20:101–110. https://doi.org/10.1016/j.addma.2017.12.007

    Article  Google Scholar 

  96. Xu JJ, Lin X, Guo PF, Hu YL, Wen XL, Xue L, Liu JR, Huang WD (2017) The effect of preheating on microstructure and mechanical properties of laser solid forming IN-738LC alloy. Mater Sci Eng A 691:71–80. https://doi.org/10.1016/j.msea.2017.03.046

    Article  Google Scholar 

  97. Rickenbacher L, Etter T, Hövel S, Wegener K (2013) High temperature material properties of IN738LC processed by selective laser melting (SLM) technology. Rapid Prototyp J 19:282–290. https://doi.org/10.1108/13552541311323281

    Article  Google Scholar 

Download references

Funding

This research work was supported by the National Natural Science Foundation of China (Grant No. 52175455), the Science and Technology Innovation Fund of Dalian (Grant No. 2020JJ26GX040), Fundamental Research Funds for the Central Universities, the Guangdong Provincial University Innovation Team Project (Grant No. 2020KCXTD012), and the 2020 Li Ka Shing Foundation Cross-Disciplinary Research (Grant No. 2020LKSFG01D).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Weiwei Liu.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, W., Liu, W., Saleheen, K.M. et al. Research and prospect of on-line monitoring technology for laser additive manufacturing. Int J Adv Manuf Technol 125, 25–46 (2023). https://doi.org/10.1007/s00170-022-10758-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-022-10758-3

Keyword

Navigation