Development of Key Design Strategies for Hot Form Quench (HFQ)

Lead Research Organisation: Imperial College London
Department Name: Design Engineering (Dyson School)

Abstract

Hot Form Quench - HFQ - is a new hot forming technology invented at Imperial College London capable of providing lightweighting solutions to the automotive and aerospace industries. HFQ enables the production of cost-effective and complex-shaped structures, with desirable geometric features including tight corner radii and sharp accent styling lines through high strength, lightweight aluminium alloys. However, there is currently insufficient knowledge on its application and design capability, meaning that HFQ can often be overlooked by structural designers and not utilised to its full potential. This work aims to develop advanced design methodologies to guide optimal design for manufacturing using HFQ technology for the first time. The work is divided into three sub-projects, aimed at tackling cutting edge design challenges for HFQ. Briefly, these are: design methodologies for producing deep drawn components with tight corners, design methodologies for forming components with a Class-A surface finish and methods to apply advanced technologies from the newly emerging field of Machine Learning to aid in the design for HFQ process.

Major tasks undertaken in the project to date include:
- a literature review to identify the intricacies and challenges currently associated with forming components using HFQ technology, and to understand key requirements challenges associated with forming Class-A surfaces
- a review of Cutting edge machine learning methods applied to solid mechanics applications, which have the potential to be applied to this work
- preliminary research including the influence of several design variables on various forming responses and a workflow for using machine learning methods for this work

Future work includes the following:
1. Further investigation into the effects of influential factors on the thickness distribution for forming corner shapes. Key sub-problems involve (HFQ conditions below mean cold tools and hot blank):
a. Summarise the effect of material, processing and geometry factors in forming box shapes with tight corners from the simulation runs in Table A.2, under isothermal conditions
b. Explore combined effects of the above factors and establish trends and sensitivities with corner forming responses, under isothermal conditions
c. Investigate the non-isothermal nature of the HFQ process when forming tight corners under various processing parameters, by considering HFQ conditions.
d. Investigate heat transfer and contact pressure effects on tight radii under HFQ conditions
e. Explore novel tooling strategies from the literature, for HFQ forming corners, such as macro textured tool surfaces (Zheng et al., 2017) and radii profiles (Wang & Masood, 2011)
2. Investigation on the effect of influential factors on the surface defects
a. Effect of material, processing and geometry factors on contact pressures at the tool-blank interface (started in Appendix B ), comparing isothermal conditions with HFQ conditions
b. Explore combined effects of the above factors on contact pressures under HFQ conditions
c. Through experimental studies (at Impression Technologies Ltd), analyse and correlate surface quality and defects with contact pressures and FE forming strains under HFQ conditions
d. Development of design methods for Class-A surfaces and conduct HFQ forming trials
3. Development of an optimal design strategy and platform for HFQ by further investigating machine learning methods for design support tools:
a. Use outcomes of 1. and 2. to divide complex, large design domains and investigate deep neural networks for metamodels of manufacturability based constraints (e.g. thinning constraints)
b. Investigation into image-based methods for complex geometries (point 1.e.) for generalisation and using CNNs to predict images of full field FE results (Zimmerling et al., 2019b)
c. Integration of the manufacturability based constraints into an optimisation platform for HFQ

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/R513052/1 01/10/2018 30/09/2023
2287635 Studentship EP/R513052/1 02/09/2019 30/05/2023 Hamid Attar