Realization and assessment of metal additive manufacturing and topology optimization for high-precision motion systems

Arnoud Delissen*, Elwin Boots, Dick Laro, Harry Kleijnen, Fred van Keulen, Matthijs Langelaar

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
14 Downloads (Pure)

Abstract

The design of high-precision motion stages, which must exhibit high dynamic performance, is a challenging task. Manual design is difficult, time-consuming, and leads to sub-optimal designs that fail to fully exploit the extended geometric freedom that additive manufacturing offers. By using topology optimization and incorporating all manufacturing steps (printing, milling, and assembly) into the optimization formulation, high-quality optimized and manufacturable designs can be obtained in an automated manner. With a special focus on overhang control, minimum feature size, and computational effort, the proposed methodology is demonstrated using a case study of an industrial motion stage, optimized for maximum eigenfrequencies. For this case study, an optimized design can be obtained in a single day, showing a substantial performance increase of around 15% as compared to a conventional design. The generated design is manufactured using laser powder-bed fusion in aluminum and experimentally validated within 1% of the simulated performance. This shows that the combination of additive manufacturing and topology optimization can enable significant gains in the high-tech industry.

Original languageEnglish
Article number103012
Number of pages14
JournalAdditive Manufacturing
Volume58
DOIs
Publication statusPublished - 2022

Keywords

  • Eigenfrequency
  • Experimental validation
  • High dynamic performance
  • Industrial application
  • Laser powder-bed fusion
  • Topology optimization

Fingerprint

Dive into the research topics of 'Realization and assessment of metal additive manufacturing and topology optimization for high-precision motion systems'. Together they form a unique fingerprint.

Cite this