Repurposing metal additive manufacturing support structures for reduction of residual stress deformation

被引:5
|
作者
Morand, Lucas M. [1 ]
Summers, Joshua D. [2 ]
Pataky, Garrett J. [1 ]
机构
[1] Clemson Univ, Dept Mech Engn, Clemson, SC 29634 USA
[2] Univ Texas Dallas, Dept Mech Engn, Richardson, TX 75080 USA
关键词
Additive manufacturing; Residual stress; DMLM; Support structures; NICKEL-BASED SUPERALLOY; TOPOLOGY OPTIMIZATION; DESIGN;
D O I
10.1007/s00170-021-08646-3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Support structures in additive manufacturing (AM) have traditionally been implemented to address process restrictions. This study repurposed the supports as design tools to be used to reduce deformation from residual stress in metal AM prints. Four geometric features were selected via industry interviews and simulations, and experimental prints were used to verify the use of new, novel supports addressing both mechanical and process limit needs. These supports reduced maximum deformation by 14.6% in a validation part simulation that contained all four features. Guidelines were created to present the new design envelopes for each geometric feature to aid in the growth of support structure documentation in AM. Using supports to reduce deformation presents a new design tool to AM engineers that allows them to retain critical part geometry and only change support design.
引用
收藏
页码:3963 / 3973
页数:11
相关论文
共 50 条
  • [41] A Review of the Residual Stress Generation in Metal Additive Manufacturing: Analysis of Cause, Measurement, Effects, and Prevention
    Bastola, Nabin
    Jahan, Muhammad P.
    Rangasamy, Nithin
    Rakurty, Chandra Sekhar
    [J]. MICROMACHINES, 2023, 14 (07)
  • [42] Effect of metal additive manufacturing residual stress on post-process machining-induced stress and distortion
    Sunny, Sumair
    Mathews, Ritin
    Gleason, Glenn
    Malik, Arif
    Halley, Jeremiah
    [J]. International Journal of Mechanical Sciences, 2021, 202-203
  • [43] Effect of metal additive manufacturing residual stress on post-process machining-induced stress and distortion
    Sunny, Sumair
    Mathews, Ritin
    Gleason, Glenn
    Malik, Arif
    Halley, Jeremiah
    [J]. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES, 2021, 202
  • [44] Residual Stress and Stress Corrosion of Alloy Materials in Laser Additive Manufacturing
    Zhang Xingshou
    Wang Qinying
    Zheng Huaibei
    Liu Tingyao
    Dong Lijin
    Xi Yuchen
    Zhang Jin
    Bai Shulin
    [J]. LASER & OPTOELECTRONICS PROGRESS, 2022, 59 (13)
  • [45] Accessibility of support structures in topology optimization for additive manufacturing
    van de Ven, Emiel
    Ayas, Can
    Langelaar, Matthijs
    Maas, Robert
    van Keulen, Fred
    [J]. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 2021, 122 (08) : 2038 - 2056
  • [46] Additive friction stir deposition: a deformation processing route to metal additive manufacturing
    Yu, Hang Z.
    Mishra, Rajiv S.
    [J]. MATERIALS RESEARCH LETTERS, 2021, 9 (02): : 71 - 83
  • [47] Simulation and validation of residual deformations in additive manufacturing of metal parts
    Mayer, Thomas
    Braendle, Gabriel
    Schoenenberger, Andreas
    Eberlein, Robert
    [J]. HELIYON, 2020, 6 (05)
  • [48] On utilizing topology optimization to design support structure to prevent residual stress induced build failure in laser powder bed metal additive manufacturing
    Cheng, Lin
    Liang, Xuan
    Bai, Jiaxi
    Chen, Qian
    Lemon, John
    To, Albert
    [J]. ADDITIVE MANUFACTURING, 2019, 27 : 290 - 304
  • [49] Effect of residual stress on mechanical properties of Triply periodic minimal surface lattice structures in Additive manufacturing
    Huang, Xinyu
    Tang, Huayuan
    Wang, Lei
    [J]. Computational Materials Science, 2024, 245
  • [50] Residual Stress Induced in Thin Plates During Additive Manufacturing
    Patterson, Eann A.
    Lambros, John
    Magana-Carranza, Rodrigo
    Sutcliffe, Christopher J.
    [J]. ADDITIVE AND ADVANCED MANUFACTURING, INVERSE PROBLEM METHODOLOGIES AND MACHINE LEARNING AND DATA SCIENCE, VOL 4, 2023, 2024, : 13 - 16