Page 29 - ESAM-1-1
P. 29

Engineering Science in
            Additive Manufacturing                                        ML in MAM monitoring and control through images



            63.  Tempelman JR, Wachtor AJ, Flynn EB, et al. Detection of   73.  Vallabh CKP, Zhao X. Melt pool temperature measurement
               keyhole pore formations in laser powder-bed fusion using   and monitoring during laser powder bed fusion based additive
               acoustic process monitoring measurements.  Addit Manuf.   manufacturing via single-camera two-wavelength imaging
               2022;55:102735.                                    pyrometry (STWIP). J Manuf Process. 2022;79:486-500.
               doi: 10.1016/j.addma.2022.102735                   doi: 10.1016/j.jmapro.2022.04.058
            64.  Li ZW, Zhang ZF, Zhang S, et al. In-situ monitoring in laser   74.  Tempelman JR, Wachtor AJ, Flynn EB, et al. Sensor fusion of
               powder bed fusion based on acoustic signal time-frequency   pyrometry and acoustic measurements for localized keyhole
               synchrosqueezing transform and multi-scale spatially   pore identification in laser powder bed fusion.  J  Mater
               interactive fusion convolutional neural network.  J  Manuf   Proces Technol. 2022;308:117656.
               Proces. 2024;126:471-486.
                                                                  doi: 10.1016/j.jmatprotec.2022.117656
               doi: 10.1016/j.jmapro.2024.07.068
                                                               75.  Mitchell JA, Ivanoff TA, Dagel D, Madison JD, Jared B.
            65.  Chen L, Yao X, Tan C,  et al.  In-situ crack and keyhole   Linking pyrometry to porosity in additively manufactured
               pore detection in laser directed energy deposition   metals. Addit Manuf. 2020;31:100946.
               through acoustic signal and deep learning.  Addit Manuf.      doi: 10.1016/j.addma.2019.100946
               2023;69:103547.
                                                               76.  Kayacan MY, Yılmaz N. An investigation on the
               doi: 10.1016/j.addma.2023.103547
                                                                  measurement of instantaneous temperatures in laser assisted
            66.  Ito K, Kusano M, Demura M, Watanabe M. Detection and   additive manufacturing by thermal imagers. Measurement.
               location of microdefects during selective laser melting by   2020;160:107825.
               wireless acoustic emission measurement.  Addit Manuf.      doi: 10.1016/j.measurement.2020.107825
               2021;40:101915.
                                                               77.  Rajaram Narayanan M, Nallusamy S. Experimental analysis
               doi: 10.1016/j.addma.2021.101915
                                                                  of aluminium alloy metal matrix composite with tungsten
            67.  Huang Y, Zhang F, Yuan J, Jia C, Ren X, Yang L. Investigation   carbide  by  in-situ method using  sem.  Rasayan J Chem.
               on surface morphology and microstructure of double-  2018;11(1):355-360.
               wire+arc additive manufactured aluminum alloys based on      doi: 10.7324/RJC.2018.1112047
               spectral analysis. J Manuf Process. 2022;84:639-651.
                                                               78.  Tian Q, Guo SH, Melder E, Bian L, Guo WH. Deep learning-
               doi: 10.1016/j.jmapro.2022.10.043
                                                                  based data fusion method for in situ porosity detection in
            68.  Lough CS, Escano LI, Qu M, et al. In-situ optical emission   laser-based additive manufacturing. J Manuf Sci Eng Trans
               spectroscopy of selective laser melting.  J  Manuf Process.   ASME. 2021;143(4):041011.
               2020;53:336-341.
                                                                  doi: 10.1115/1.4048957
               doi: 10.1016/j.jmapro.2020.02.016
                                                               79.  Mazzarisi M, Angelastro A, Latte M, Colucci T, Palano F,
            69.  Liu  S,  Liu W, Harooni  M,  Ma  J, Kovacevic  R.  Real-time   Campanelli SL. Thermal monitoring of laser metal
               monitoring of laser hot-wire cladding of Inconel 625. Optics   deposition strategies using infrared thermography. J Manuf
               Laser Technol. 2014;62:124-134.                    Process. 2023;85:594-611.
               doi: 10.1016/j.optlastec.2014.03.007               doi: 10.1016/j.jmapro.2022.11.067
            70.  Montazeri M, Nassar AR, Dunbar AJ, Rao P. In-process   80.  Hu Y, Chen H, Liang X, Xie J. Monitoring molten pool
               monitoring of porosity in additive manufacturing using   temperature, grain size and molten pool plasma with
               optical emission spectroscopy. IISE Trans. 2020;52(5):500-515.  integrated area of the spectrum during laser additive
                                                                  manufacturing. J Manuf Process. 2021;64:851-860.
               doi: 10.1080/24725854.2019.1659525
                                                                  doi: 10.1016/j.jmapro.2021.01.040
            71.  Pandiyan V, Drissi-Daoudi R, Shevchik S,  et al. Deep
               transfer learning of additive manufacturing mechanisms   81.  Escano LI, Clark SJ, Chuang AC, et al. An electron beam
               across materials in metal-based laser powder bed fusion   melting system for  in-situ synchrotron X-ray monitoring.
               process. J Mater Process Technol. 2022;303:117531.  Addit Manuf Lett. 2022;3:100094.
               doi: 10.1016/j.jmatprotec.2022.117531              doi: 10.1016/j.addlet.2022.100094
            72.  Smoqi Z, Gaikwad A, Bevans B,  et al. Monitoring and   82.  Yan Z, Liu S, Sun Z, Li K, Su N, Yang G.  In situ  X-ray
               prediction of porosity in laser powder bed fusion using   imaging and quantitative analysis of balling during laser
               physics-informed meltpool signatures and machine   powder bed fusion of 316L at high layer thickness. Mater
               learning. J Mater Process Technol. 2022;304:117550.  Des. 2024;248:113442.
               doi: 10.1016/j.jmatprotec.2022.117550              doi: 10.1016/j.matdes.2024.113442


            Volume 1 Issue 1 (2025)                         23                             doi: 10.36922/esam.8548
   24   25   26   27   28   29   30   31   32   33   34