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International Journal of AI
            for Material and Design                                                ML for quality improvement in L-PBF



               of quality repeatability in metal laser powder bed fusion      doi: 10.1016/j.apsusc.2013.05.081
               additive manufacturing. Mater Des. 2021;203:109606.
                                                               62.  Schweier M, Heins JF, Haubold MW, Zaeh MF. Spatter
               doi: 10.1016/j.matdes.2021.109606                  formation  in  laser  welding  with  beam  oscillation.  Physics
                                                                  Proc. 2013;41:20-30.
            53.  Feng S, Chen Z, Bircher B, Ji Z, Nyborg L, Bigot S. Predicting
               laser  powder  bed  fusion defects through in-process      doi: 10.1016/j.phpro.2013.03.047
               monitoring data and machine learning.  Mater  Des.   63.  Luo  S,  Ma  X, Xu J,  Li  M,  Cao  L.  Deep  learning  based
               2022;222:111115.                                   monitoring of spatter behavior by the acoustic signal in
               doi: 10.1016/j.matdes.2022.111115                  selective laser melting. Sensors (Basel). 2021;21(21):7179.
            54.  Paulson NH, Gould B, Wolff SJ, Stan M, Greco AC.      doi: 10.3390/s21217179
               Correlations between thermal history and keyhole porosity   64.  Wang L, Chen X, Henkel D, Jin R. Pyramid ensemble
               in laser powder bed fusion. Addit Manuf. 2020;34:101213.  convolutional  neural  network  for  virtual  computed
               doi: 10.1016/j.addma.2020.101213                   tomography image prediction in a selective laser melting
                                                                  process. J Manuf Sci Eng. 2021;143(12):121003.
            55.  Yuan B, Giera B, Guss G, Matthews I, Mcmains S. Semi-
               Supervised Convolutional Neural Networks for  In-situ      doi: 10.1115/1.4051077
               Video Monitoring  of Selective Laser Melting. In:  2019   65.  Yadav P, Rigo O, Arvieu C, Le Guen E, Lacoste E. In situ
               IEEE Winter Conference on Applications of Computer Vision   monitoring systems of the SLM process: On the need to
               (WACV). United States, IEEE 2019, p744-753.        develop machine learning models for data processing.
               doi: 10.1109/WACV.2019.00084                       Crystals. 2020;10(6):524.
            56.  Li  J,  Cao  L,  Xu  J,  Wang  S, Zhou  Q.  In  situ  porosity      doi: 10.3390/cryst10060524
               intelligent classification of selective laser melting based on   66.  Terry BS, Baucher B, Chaudhary A, Chakraborty S. Active
               coaxial monitoring and image processing.  Measurement.   monitoring of selective laser melting process by training an
               2022;187:110232.                                   artificial neural net classifier on layer-by-layer surface laser
                                                                  profilometry data.  In review. Int J Adv Manufact Technol.
               doi: 10.1016/j.measurement.2021.110232
                                                                  2021.
            57.  Li J, Zhou Q, Huang X, Li M, Cao L. In situ quality inspection
               with  layer-wise  visual  images  based  on  deep  transfer      doi: 10.21203/rs.3.rs-893873/v1
               learning during selective laser melting.  J  Intell  Manuf.   67.  Snow Z, Diehl B, Reutzel EW, Nassar A. Toward in-situ flaw
               2023;34(2):853-867.                                detection in laser powder bed fusion additive manufacturing
                                                                  through layerwise imagery and machine learning. J Manuf
               doi: 10.1007/s10845-021-01829-5
                                                                  Syst. 2021;59:12-26.
            58.  Wang H, Li B, Xuan FZ. Acoustic emission for  in situ      doi: 10.1016/j.jmsy.2021.01.008
               process monitoring of selective laser melting additive
               manufacturing based on machine learning and improved   68.  Pandiyan V, Drissi-Daoudi R, Shevchik S,  et al. Semi-
               variational modal decomposition. Int J Adv Manuf Technol.   supervised monitoring of laser powder bed fusion
               2022;122(5-6):2277-2292.                           process based on acoustic emissions.  Virtual Phys
                                                                  Prototyp. 2021;16(4):481-497.
               doi: 10.1007/s00170-022-10032-6
                                                                  doi: 10.1080/17452759.2021.1966166
            59.  Ansari MA, Crampton A, Garrard R, Cai B, Attallah M.
               A  convolutional neural network (CNN) classification to   69.  Okaro IA, Jayasinghe S, Sutcliffe C, Black K, Paoletti P,
               identify the presence of pores in powder bed fusion images.   Green PL. Automatic fault detection for laser powder-bed
               Int J Adv Manuf Technol. 2022;120(7-8):5133-5150.  fusion using semi-supervised machine learning.  Addit
                                                                  Manuf. 2019;27:42-53.
               doi: 10.1007/s00170-022-08995-7
                                                                  doi: 10.1016/j.addma.2019.01.006
            60.  Drissi-Daoudi R, Pandiyan V, Logé R, Shevchik  S,
               Masinelli G, Ghasemi-Tabasi H,  et al. Differentiation of   70.  Mohammadi MG, Elbestawi M. Real time monitoring in
               materials and laser powder bed fusion processing regimes   L-PBF using a machine learning approach.  Proc Manuf.
               from  airborne  acoustic  emission combined with  machine   2020;51:725-731.
               learning. Virtual Phys Prototyp. 2022;17(2):181-204.     doi: 10.1016/j.promfg.2020.10.102
               doi: 10.1080/17452759.2022.2028380              71.  Li J, Cao L, Zhou Q, Liu H, Zhang X. Imbalanced quality
            61.  Zhang MJ, Chen GY, Zhou Y, Li SC, Deng H. Observation   monitoring of selective laser melting using acoustic and
               of spatter formation mechanisms in high-power fiber laser   photodiode signals. J Manuf Process. 2023;105:14-26.
               welding of thick plate. Appl Surface Sci. 2013;280:868-875.     doi: 10.1016/j.jmapro.2023.09.037


            Volume 1 Issue 1 (2024)                         42                      https://doi.org/10.36922/ijamd.2301
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