A study on power-controlled wire-arc additive manufacturing using a data-driven surrogate model

被引:9
|
作者
Israr, Rameez [1 ]
Buhl, Johannes [1 ]
Bambach, Markus [2 ]
机构
[1] Brandenburg Tech Univ Cottbus, Chair Mech Design & Mfg, Konrad Wachsmann Allee 17, D-03046 Cottbus, Germany
[2] Swiss Fed Inst Technol, Adv Mfg Lab, Leonhardstr 27, CH-8092 Zurich, Switzerland
关键词
Wire-arc additive manufacturing; Numerical analysis; Experimental investigation; Welding parameters; Welding power; Weld-bead size; Heat accumulation; Pause time; THIN-WALLED PARTS; MECHANICAL-PROPERTIES; MICROSTRUCTURE; SIMULATION; DESIGN; ZONE;
D O I
10.1007/s00170-021-07358-y
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Wire-arc additive manufacturing (WAAM) provides an alternative for the production of various metal products needed in medium to large batch sizes due to its high deposition rates. However, the cyclic heat input in WAAM may cause local overheating. To avoid adverse effects on the performance of the part, interlayer dwelling and active cooling are used, but these measures increase the process time. Alternatively, the temperature during the WAAM process could be controlled by optimizing the welding power. The present work aims at introducing and implementing a novel temperature management approach by adjusting the weld-bead cross-section along with the welding power to reduce the heat accumulation in the WAAM process. The temperature evolution during welding of weld beads of different cross-sections is investigated and a database of the relation between optimal welding power for beads of various sizes and different pre-heating temperatures was established. The numerical results are validated experimentally with a block-shaped geometry. The results show that by the proposed method, the test shape made was welded with lower energy consumption and process time as compared to conventional constant-power WAAM. The proposed approach efficiently manages the thermal input and reduces the need for pausing the process. Hence, the defects related to heat accumulation might be reduced, and the process efficiency increased.
引用
收藏
页码:2133 / 2147
页数:15
相关论文
共 50 条
  • [41] Study of impact strength of C-Mn-Si composition metal after wire-arc additive manufacturing (WAAM)
    Balanovskiy, A. E.
    Astafyeva, N. A.
    Kondratyev, V. V.
    Karlina, Yu. I.
    CIS IRON AND STEEL REVIEW, 2022, 24 : 67 - 73
  • [42] Comparative Study on Wire-Arc Additive Manufacturing and Conventional Casting of Al–Si Alloys:Porosity,Microstructure and Mechanical Property
    Yueling Guo
    Qifei Han
    Jinlong Hu
    Xinghai Yang
    Pengcheng Mao
    Junsheng Wang
    Shaobo Sun
    Zhi He
    Jiping Lu
    Changmeng Liu
    Acta Metallurgica Sinica(English Letters), 2022, 35 (03) : 475 - 485
  • [43] Comparative Study on Wire-Arc Additive Manufacturing and Conventional Casting of Al–Si Alloys: Porosity, Microstructure and Mechanical Property
    Yueling Guo
    Qifei Han
    Jinlong Hu
    Xinghai Yang
    Pengcheng Mao
    Junsheng Wang
    Shaobo Sun
    Zhi He
    Jiping Lu
    Changmeng Liu
    Acta Metallurgica Sinica (English Letters), 2022, 35 : 475 - 485
  • [44] Optimal data-driven control of manufacturing processes using reinforcement learning: an application to wire arc additive manufacturing (Jan, 10.1007/s10845-023-02307-w, 2024)
    Mattera, Giulio
    Caggiano, Alessandra
    Nele, Luigi
    JOURNAL OF INTELLIGENT MANUFACTURING, 2024, : 1311 - 1311
  • [45] Data-Driven Model for Predicting Tensile Properties of Wire Arc Additive Manufactured 316L Steels and Its Validation
    Ramesh Mamedipaka
    Shivraman Thapliyal
    Journal of Materials Engineering and Performance, 2024, 33 : 1083 - 1091
  • [46] Data-Driven Model for Predicting Tensile Properties of Wire Arc Additive Manufactured 316L Steels and Its Validation
    Mamedipaka, Ramesh
    Thapliyal, Shivraman
    JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE, 2024, 33 (03) : 1083 - 1091
  • [47] A Hybrid Deep Learning Model for Layer-Wise Melt Pool Temperature Forecasting in Wire-Arc Additive Manufacturing Process
    Nalajam, Pavan Kumar
    Varadarajan, Ramesh
    IEEE ACCESS, 2021, 9 : 100652 - 100664
  • [48] Experimental investigations on microstructure and mechanical properties of wall structure of SS309L using wire-arc additive manufacturing
    Chaudhari, Rakesh
    Khanna, Sakshum
    Vora, Jay
    Patel, Vivek
    JOURNAL OF ADVANCED JOINING PROCESSES, 2024, 9
  • [49] Trailblazing multi-material structure: Niobium alloy to tungsten-copper composite using wire-arc additive manufacturing
    Karim, Md Abdul
    Jeon, Yongho
    Kim, Duck Bong
    MATERIALS LETTERS, 2024, 375
  • [50] A multi-tier layer-wise thermal management study for long-scale wire-arc additive manufacturing
    Srivastava, Shekhar
    Garg, Rajiv Kumar
    Sachdeva, Anish
    Sharma, Vishal S.
    JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2022, 306