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  • 标题:Intelligent Scan Sequence Optimization for Uniform Temperature Distribution in Laser Powder Bed Fusion using a Control Theoretic Approach
  • 本地全文:下载
  • 作者:Keval S. Ramani ; Chinedum E. Okwudire
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:20
  • 页码:503-508
  • DOI:10.1016/j.ifacol.2021.11.222
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractParts produced by laser powder bed fusion (LPBF) additive manufacturing are prone to residual stresses, deformations, and other defects linked to nonuniform temperature distribution during the process. Several works have highlighted the important role scan sequence plays in achieving uniform temperature distribution in LPBF. However, scan sequence continues to be determined offline based on trial-and-error or heuristics, which are neither optimal nor generalizable. Towards addressing these weaknesses, we present, for the first time, an approach for intelligent online scan sequence optimization to achieve uniform temperature distribution in LPBF using a control theoretic approach. The thermal dynamics of the LPBF process is modeled using the finite difference method and the next best feature (for example, stripe or island) that minimizes a thermal uniformity metric is found using a control theoretic approach. In simulations, the proposed approach yields up to 8.4 times improvement in thermal uniformity compared to existing heuristic approaches.
  • 关键词:KeywordsAdditive manufacturingLaser powder bed fusionTemperature distributionScanning strategiesFinite difference methodLinear systemsOptimal control
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