Optimization of forging processes using finite element simulations

Martijn H.A. Bonte, Lionel Fourment, Tien-tho Do, A.H. van den Boogaard*, J. Huétink

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

57 Citations (Scopus)
168 Downloads (Pure)


During the last decades, simulation software based on the Finite Element Method (FEM) has significantly contributed to the design of feasible forming processes. Coupling FEM to mathematical optimization algorithms offers a promising opportunity to design optimal metal forming processes rather than just feasible ones. In this paper Sequential Approximate Optimization (SAO) for optimizing forging processes is discussed. The algorithm incorporates time-consuming nonlinear FEM simulations. Three variants of the SAO algorithm—which differ by their sequential improvement strategies—have been investigated and compared to other optimization algorithms by application to two forging processes. The other algorithms taken into account are two iterative algorithms (BFGS and SCPIP) and a Metamodel Assisted Evolutionary Strategy (MAES). It is essential for sequential approximate optimization algorithms to implement an improvement strategy that uses as much information obtained during previous iterations as possible. If such a sequential improvement strategy is used, SAO provides a very efficient algorithm to optimize forging processes using time-consuming FEM simulations.
Original languageEnglish
Pages (from-to)797-810
JournalStructural and multidisciplinary optimization
Issue number5
Publication statusPublished - 2010


  • Sequential approximate optimization
  • Optimization algorithms
  • Forming processes
  • Finite element simulations
  • Forging


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