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Title: A Robust Optimisation Strategy for Metal Forming Processes

Abstract

Robustness, reliability, optimisation and Finite Element simulations are of major importance to improve product quality and reduce costs in the metal forming industry. In this paper, we propose a robust optimisation strategy for metal forming processes. The importance of including robustness during optimisation is demonstrated by applying the robust optimisation strategy to an analytical test function and an industrial hydroforming process, and comparing it to deterministic optimisation methods. Applying the robust optimisation strategy significantly reduces the scrap rate for both the analytical test function and the hydroforming process.

Authors:
; ;  [1]
  1. University of Twente, P.O. Box 217, 7500 AE Enschede (Netherlands)
Publication Date:
OSTI Identifier:
21061718
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 908; Journal Issue: 1; Conference: NUMIFORM 2007: 9. international conference on numerical methods in industrial forming processes, Porto (Portugal), 17-21 Jun 2007; Other Information: DOI: 10.1063/1.2740859; (c) 2007 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ALLOYS; COMPUTERIZED SIMULATION; FINITE ELEMENT METHOD; MATERIALS WORKING; METALS; OPTIMIZATION; RELIABILITY

Citation Formats

Bonte, M. H. A., Boogaard, A. H. van den, and Ravenswaaij, R. van. A Robust Optimisation Strategy for Metal Forming Processes. United States: N. p., 2007. Web. doi:10.1063/1.2740859.
Bonte, M. H. A., Boogaard, A. H. van den, & Ravenswaaij, R. van. A Robust Optimisation Strategy for Metal Forming Processes. United States. doi:10.1063/1.2740859.
Bonte, M. H. A., Boogaard, A. H. van den, and Ravenswaaij, R. van. Thu . "A Robust Optimisation Strategy for Metal Forming Processes". United States. doi:10.1063/1.2740859.
@article{osti_21061718,
title = {A Robust Optimisation Strategy for Metal Forming Processes},
author = {Bonte, M. H. A. and Boogaard, A. H. van den and Ravenswaaij, R. van},
abstractNote = {Robustness, reliability, optimisation and Finite Element simulations are of major importance to improve product quality and reduce costs in the metal forming industry. In this paper, we propose a robust optimisation strategy for metal forming processes. The importance of including robustness during optimisation is demonstrated by applying the robust optimisation strategy to an analytical test function and an industrial hydroforming process, and comparing it to deterministic optimisation methods. Applying the robust optimisation strategy significantly reduces the scrap rate for both the analytical test function and the hydroforming process.},
doi = {10.1063/1.2740859},
journal = {AIP Conference Proceedings},
number = 1,
volume = 908,
place = {United States},
year = {Thu May 17 00:00:00 EDT 2007},
month = {Thu May 17 00:00:00 EDT 2007}
}
  • Robustness, reliability, optimisation and Finite Element simulations are of major importance to improve product quality and reduce costs in the metal forming industry. In this paper, we review several possibilities for combining these techniques and propose a robust optimisation strategy for metal forming processes. The importance of including robustness during optimisation is demonstrated by applying the robust optimisation strategy to an analytical test function: for constrained cases, deterministic optimisation will yield a scrap rate of about 50% whereas the robust counterpart reduced this to the required 3{sigma} reliability level.
  • Robustness, optimization and Finite Element (FE) simulations are of major importance for achieving better products and cost reductions in the metal forming industry. In this paper, a metamodel-based robust optimization strategy is proposed for metal forming processes. The applicability of the strategy is demonstrated by application to an analytical test function and an industrial V-bending process. The results of both applications underline the importance of including uncertainty and robustness explicitly in the optimization procedure.
  • Coupling Finite Element (FEM) simulations to mathematical optimisation techniques provides a high potential to improve industrial metal forming processes. In order to optimise these processes, all kind of optimisation problems need to be mathematically modelled and subsequently solved using an appropriate optimisation algorithm. Although the modelling part greatly determines the final outcome of optimisation, the main focus in most publications until now was on the solving part of mathematical optimisation, i.e. algorithm development. Modelling is generally performed in an arbitrary way.In this paper, we propose an optimisation strategy for metal forming processes using FEM. It consists of three stages: amore » structured methodology for modelling optimisation problems, screening for design variable reduction, and a generally applicable optimisation algorithm. The strategy is applied to solve manufacturing problems for an industrial deep drawing process.« less
  • Robust design of forming processes using numerical simulations is gaining attention throughout the industry. In this work, it is demonstrated how robust optimization can assist in further stretching the limits of metal forming processes. A deterministic and a robust optimization study are performed, considering a stretch-drawing process of a hemispherical cup product. For the robust optimization study, both the effect of material and process scatter are taken into account. For quantifying the material scatter, samples of 41 coils of a drawing quality forming steel have been collected. The stochastic material behavior is obtained by a hybrid approach, combining mechanical testingmore » and texture analysis, and efficiently implemented in a metamodel based optimization strategy. The deterministic and robust optimization results are subsequently presented and compared, demonstrating an increased process robustness and decreased number of product rejects by application of the robust optimization approach.« less