Hot forming of boron steels using heated and cooled tooling for tailored properties

George, Ryan; Bardelcik, Alexander; Worswick, Michael J.

doi:10.1016/j.jmatprotec.2012.06.028

Cited by 168 publications

(96 citation statements)

References 9 publications

(13 reference statements)

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“…At room temperature, high strength steel and aluminium alloys have low formability, which leads to high springback and poor surface quality of formed components. To deal with this problem, warm and hot forming technologies have been developed, which are hot stamping and cold die quenching (also termed as press hardening) for quenchable steel [4] and solution heat treatment, forming and in-die quenching (HFQ ® ) of lightweight alloys [5]. The hot stamping and cold die quenching process, abbreviated to hot stamping, is…”

Section: Introductionmentioning

confidence: 99%

Formability evaluation for sheet metals under hot stamping conditions by a novel biaxial testing system and a new materials model

Shao

Lin

et al. 2017

International Journal of Mechanical Sciences

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Published: Z. Shao, N. Li, J. Lin, T. Dean, 2017, Formability evaluation for sheet metals under hot stamping conditions by a novel biaxial testing system and a new materials model, Int. J. Mech. Sci., 120, pp149-158. AbstractHot stamping and cold die quenching has been developed in forming complex shaped structural components of metals. The aim of this study is the first attempt to develop unified viscoplastic damage constitutive equations to describe the thermo-mechanical response of the metal and to predict the formability of the metal for hot stamping applications. Effects of parameters in the damage evolution equation on the predicted forming limit curves were investigated. Test facilities and methods need to be established to obtain experimental formability data of metals in order to determine and verify constitutive equations. However, conventional experimental approaches used to determine forming limit diagrams (FLDs) of sheet metals under different linear strain paths are not applicable to hot stamping conditions due to the requirements of rapid heating and cooling processes prior to forming. A novel planar biaxial testing system was proposed before and was improved and used in this work for formability tests of aluminium alloy 6082 at various temperatures, strain rates and strain paths after heating, soaking and rapid cooling processes. The key dimensions and features of cruciform specimens adopted for the determination of forming limit under various strain paths were developed, optimised and verified based on the previous designs and the determined heating and cooling method [1]. The digital image correlation (DIC) system was adopted to record strain fields of a specimen throughout the deformation history. Material constants in constitutive equations were determined from the formability test results of AA6082 for the prediction of forming limit of alloys under hot stamping conditions. This research, for the first time, enabled forming limit data of an alloy to be generated at various temperatures, strain rates and strain paths and forming limits to be predicted under hot stamping conditions.

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Section: Introductionmentioning

confidence: 99%

Formability evaluation for sheet metals under hot stamping conditions by a novel biaxial testing system and a new materials model

Shao

Lin

et al. 2017

International Journal of Mechanical Sciences

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“…The hot stamping by using the tailored die quenching was developed, and it changed the mechanical properties of components at different regions by the various cooling rates. [8][9][10][11][12] This method does not need changes on the blank production process, but it increases the complexity of the mold design and reduces the production efficiency. Using an additional annealing was a new method for producing tailored components as well, by which a soft zone at the components can be acquired after hot stamping.…”

Section: Heating Parameters Optimization Of Hot Stamping By Partitionmentioning

confidence: 99%

Heating Parameters Optimization of Hot Stamping by Partition Heating for Tailored Properties

Wang

Zhou

et al. 2017

ISIJ International

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“…Researchers have come up with an innovative solution to this problem where local sheet metal cooling rates are varied by dividing the tooling into heated and cooled zones. Doing so introduces local regions within hot stamped parts which have a softer and more ductile microstructure as compared to the rest of the part [9][10][11]. This process is known as tailored hot stamping and it allows for tailoring of the local mechanical properties in the different regions of the hot stamped parts to fully optimize the energy absorption characteristic of the formed part for improved crash performance and light weighting.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network (ANN) based microstructural prediction model for 22MnB5 boron steel during tailored hot stamping

Chokshi

Dashwood

Hughes

2017

Computers & Structures

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Abstract:Because of demand for lower emissions and better crashworthiness, the use of hot stamped 22MnB5 boron steel has greatly increased in manufacturing of automobile components. However, for many applications it is required that only certain regions in hot stamped parts are fully hardened whereas other regions need be more ductile. The innovative process of tailored hot stamping does this by controlling the localized microstructures through tailored cooling rates by dividing the tooling into heated and cooled zones. A barrier to optimal application of this technique is the lack of reliable phase distribution prediction model for the process.We present a novel Artificial Neural Network (ANN) based phase distribution prediction model for tailored hot stamping. The model was developed and validated using data generated from extensive thermo-mechanical physical simulation experiments and instrumented nanoindentation based phase quantification method. Advanced statistical techniques were used for preventing overfitting, for making the optimal use of available experimental data and for quantification of prediction uncertainty. The final predictions made by the ANN model during its independent validation have shown good agreement with the experimentally generated data and have a RMS prediction error of just 7.7%, which is a significant improvement over the existing models.

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Hot forming of boron steels using heated and cooled tooling for tailored properties

Cited by 168 publications

References 9 publications

Formability evaluation for sheet metals under hot stamping conditions by a novel biaxial testing system and a new materials model

Formability evaluation for sheet metals under hot stamping conditions by a novel biaxial testing system and a new materials model

Heating Parameters Optimization of Hot Stamping by Partition Heating for Tailored Properties

Artificial Neural Network (ANN) based microstructural prediction model for 22MnB5 boron steel during tailored hot stamping

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