Page 33 - ESAM-1-1

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

(DED) process with in situ melt-pool monitoring. Int J Adv 154. Rawat D, Gupta MK, Sharma A. Intelligent control of robotic
Manuf Technol. 2023;125(1-2):357-368. manipulators: A comprehensive review. Spatial Inform Res.
2023;31(3):345-357.
doi: 10.1007/s00170-022-10711-4
doi: 10.1007/s41324-022-00500-2
145. Chen RM, Sodhi M, Imani M, Khanzadeh M, Yadollahi A,
Imani F. Brain-inspired computing for in-process melt pool 155. Rezaeifar H, Elbestawi M. Minimizing the surface roughness
characterization in additive manufacturing. CIRP J Manuf in L-PBF additive manufacturing process using a combined
Sci Technol. 2023;41:380-390. feedforward plus feedback control system. Int J Adv Manuf
Technol. 2022;121(11-12):7811-7831.
doi: 10.1016/j.cirpj.2022.12.009
doi: 10.1007/s00170-022-09902-w
146. Balaraman RK, Hussain S, Ong JK, Tan QY, Raghavan N.
Feature-driven density prediction of maraging steel additively 156. Devesse W, De Baere D, Hinderdael M, Guillaume P.
manufactured samples using pyrometer sensor and Hardware-in-the-loop control of additive manufacturing
supervised machine learning. IEEE Access. 2024;12:172892- processes using temperature feedback. J Laser Appl.
172909. 2016;28(2):022302.
doi: 10.1109/access.2024.3486731 doi: 10.2351/1.4943911
147. Yang Z, Zhu L, Dun Y, et al. In-situ monitoring of 157. Miao L, Xing F, Chai Y. Closed loop control of melt pool
the melt pool dynamics in ultrasound-assisted metal width in laser directed energy deposition process based on
3D printing using machine learning. Virtual Phys PSO-LQR. IEEE Access. 2023;11:78170-78181.
Prototyp. 2023;18(1):e2251453. doi: 10.1109/ACCESS.2023.3292789
doi: 10.1080/17452759.2023.2251453 158. Gibson BT, Bandari YK, Richardson BS, et al. Melt pool size
148. Chen L, Yao X, Xu P, Moon SK, Bi G. Rapid surface defect control through multiple closed-loop modalities in laser-
identification for additive manufacturing with in-situ wire directed energy deposition of Ti-6Al-4V. Addit Manuf.
point cloud processing and machine learning. Virtual Phys 2020;32:100993.
Prototyp. 2021;16(1):50-67. doi: 10.1016/j.addma.2019.100993
doi: 10.1080/17452759.2020.1832695 159. Bernauer C, Zapata A, Zaeh MF. Toward defect-free
149. Li H, Yan SH, Fu Y. Data-fusion for in-situ monitoring and components in laser metal deposition with coaxial wire
molten state identification during LPBF of NiCoCr medium- feeding through closed-loop control of the melt pool
entropy alloy. Sci Rep. 2024;14(1):14697. temperature. J Laser Appl. 2022;34(4):042044.
doi: 10.1038/s41598-024-65545-9 doi: 10.2351/7.0000773
150. Behnke M, Guo S, Guo WG. Comparison of early stopping 160. Smoqi Z, Bevans BD, Gaikwad A, et al. Closed-loop control
neural network and random forest for in-situ quality of meltpool temperature in directed energy deposition.
prediction in laser based additive manufacturing. Proc Mater Des. 2022;215:110508.
Manuf. 2021;53:656-663. doi: 10.1016/j.matdes.2022.110508
doi: 10.1016/j.promfg.2021.06.065 161. Cruz JG, Torres EM, Absi Alfaro SC. A methodology for
151. Ren W, Mazumder J. In-situ porosity recognition for laser modeling and control of weld bead width in the GMAW
additive manufacturing of 7075-Al alloy using plasma process. J Braz Soc Mechan Sci Eng. 2015;37(5):1529-1541.
emission spectroscopy. Sci Rep. 2020;10(1):19493. doi: 10.1007/s40430-014-0299-8
doi: 10.1038/s41598-020-75131-4 162. Kershaw J, Yu R, Zhang Y, Wang P. Hybrid machine learning-
152. Kumar A, Sarma R, Bag S, Srivastava VC, Kapil S. Physics- enabled adaptive welding speed control. J Manuf Process.
informed machine learning models for the prediction of 2021;71:374-383.
transient temperature distribution of ferritic steel in directed doi: 10.1016/j.jmapro.2021.09.023
energy deposition by cold metal transfer. Sci Technol Weld 163. Zhang YY, Xiong J, Li DY, Zhang GJ. Height control in
Join. 2023;28(9):914-922.
GMA-AM using external wire as controlling variable. Mater
doi: 10.1080/13621718.2023.2247242 Manuf Process. 2023;38(8):971-979.
153. Cao X, Duan C, Luo X, et al. Physics-informed machine doi: 10.1080/10426914.2022.2089892
learning approach for molten pool morphology prediction
and process evaluation in directed energy deposition of 164. Tang SY, Wang GL, Zhang HO. In situ 3D monitoring
and control of geometric signatures in wire and arc
12CrNi2 alloy steel. J Manuf Process. 2024;119:806-826.
additive manufacturing. Topography Metrol Properties.
doi: 10.1016/j.jmapro.2024.04.023 2019;7(2):025013.

Volume 1 Issue 1 (2025) 27 doi: 10.36922/esam.8548