Optimal design of metal forming die surfaces with evolution strategies

Schenk, Olaf; Hillmann, M.

doi:10.1016/j.compstruc.2004.03.055

Cited by 57 publications

(21 citation statements)

References 9 publications

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“…However, the rather large number of function evaluations that is expected to be necessary using these algorithms is regarded as a serious drawback (Emmerich et al 2002). Several authors have applied genetic and evolutionary algorithms to optimise metal forming processes, see Abedrabbo et al (2004), António et al (2004), Castro et al (2004), Do et al (2004), Fourment et al (2005a, b), Poursina et al (2003), Schenk and Hillmann (2004), Sousa et al (2003), and Weyler et al (2004).…”

Section: Solvingmentioning

confidence: 99%

“…Ben Ayed et al (2004aAyed et al ( , b, 2005, Breitkopf et al (2005), Cao et al (2001), Debray et al (2004), Jansson (2002), Jansson et al 2005, Kim et al (2001a, Kleinermann (2001), Kleinermann and Ponthot (2003), Lenoir and Boudeau (2003), Liew et al (2004), Naceur et al (2001Naceur et al ( , 2003Naceur et al ( , 2004a, Ponthot and Kleinermann (2005), Schenk and Hillmann (2004), Sheng et al (2004), Shi et al (2004), Lin et al (2002) and Strano and Carrino (2004) apply optimisation techniques to deep drawing; Abedrabbo et al (2004), Aydemir et al (2005), Di Lorenzo et al (2004), Endelt (2003), Endelt and Nielsen (2001), Fann and Hsiao (2003), Jirathearanat and Altan (2004), Johnson et al (2004), Labergère and Gelin (2004a, b), Ray and Mac Donald (2004), Sillekens and Werkhoven (2001), Weyler et al (2004) and Yang et al (2001) to hydroforming; Carrino et al (2003a, b) and Kim et al (2001b) to superplastic forming; Byon and Hwang (2001) and Lin et al (2003) to extrusion; and António et al (2004)...…”

Section: Introductionmentioning

confidence: 99%

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An optimisation strategy for industrial metal forming processes

Bonte

Boogaard

Huétink

2008

Struct Multidisc Optim

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Product improvement and cost reduction have always been important goals in the metal forming industry. The rise of finite element (FEM) simulations for processes has contributed to these goals in a major way. More recently, coupling FEM simulations to mathematical optimisation techniques has shown the potential to make a further giant contribution to product improvement and cost reduction. Much research on the optimisation of metal forming processes has been published during the last couple of years. Although the results are impressive, the optimisation techniques are generally only applicable to specific optimisation problems for specific products and specific metal forming processes. As a consequence, applying optimisation techniques to other metal forming problems requires a lot of optimisation expertise, which forms a barrier for more general industrial application of these techniques. In this paper, we overcome this barrier by proposing a generally applicable optimisation strategy that makes use of FEM simulations of metal forming processes. It consists of a structured methodology for modelling optimisation problems related to metal forming. Subsequently, screening is applied to reduce the size of the optimisation problem by selecting only the most important design variables. Finally, the reduced optimisation problem is solved by an efficient optimisation algorithm. The strategy is generally applicable in a sense that it is not constrained to a certain type of metal forming problem, product or process. Also, any FEM code may be included in the strategy. the structured approach for modelling and solving optimisation problems should enable non-optimisation specialists to apply optimisation techniques to improve their products and processes. The optimisation strategy has been successfully applied to a hydroforming process, which demonstrates the potential of the optimisation of metal forming processes in general and more specific the proposed optimisation strategy.

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Section: Solvingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An optimisation strategy for industrial metal forming processes

Bonte

Boogaard

Huétink

2008

Struct Multidisc Optim

View full text Add to dashboard Cite

show abstract

“…All these tasks require tacit knowledge (Polanyi, 1958) and, thus, design time is considerable. Therefore, this study applies CBR to locate a similar case (Schenk & Hillmann, 2004) to accelerate design time. This study combines CBR when designing a die face for a sheet metal panel with KBE (Fig.…”

Section: Application Of Designing With Case-based Reasoningmentioning

confidence: 99%

Knowledge-Based Engineering Supporting Die Face Design of Automotive Panels

You¹,

Yang²,

Wang³

2011

Industrial Design - New Frontiers

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“…Much research on the optimisation of metal forming processes has been published during the last couple of years, see e.g. [1]. Most of this research focussed on the solving part of optimisation, i.e.…”

Section: Introductionmentioning

confidence: 99%

Modelling, screening, and solving of optimisation problems: Application to industrial metal forming processes

Bonte

Boogaard

Veldman³

2007

AIP Conference Proceedings

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Abstract. 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: a 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.

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Optimal design of metal forming die surfaces with evolution strategies

Cited by 57 publications

References 9 publications

An optimisation strategy for industrial metal forming processes

An optimisation strategy for industrial metal forming processes

Knowledge-Based Engineering Supporting Die Face Design of Automotive Panels

Modelling, screening, and solving of optimisation problems: Application to industrial metal forming processes

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