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University Research

Since 2014, Sarginsons has been a development partner at BCAST at Brunel University, LiME (Future Liquid Metal Engineering Hub), the AMCC (Advanced Metal Casting Centre) the AMPC (the Advanced Metal Processing Centre) and the EPSRC (Engineering and Physical Sciences Research Centre).

Sarginsons has worked on research projects with Sheffield, Birmingham, Warwick, Imperial and several other universities, alongside many automotive and aerospace OEMs. This culminated in 2024 with Sarginsons leading a global consortium with, PIVOT, in applying for a £3m research grant into low carbon aluminium alloys, a combined topological simulation and solidification software package and industrialisation of casting technologies.

If approved PIVOT will totally change the way castings are designed, as well as how they look. It will enable OEMSs to design better castings that are lighter, cheaper and more flexible with near zero carbon content. Sarginsons offers its clients a totally different service from any other foundry.

PIVOT

PIVOT is a multi-national consortium, led by Sarginsons, that seeks a £3m grant, from Innovate, to research three areas that could totally change aluminium casting.

PIVOT comprises 3 core objectives. The development of a software programme that combines metal solidification, digital twin simulations and topological optimisation. The development of new casting methodologies to allow industrialisation of the radical new designs the new software will produce. And the development of a new low carbon aluminium alloy.

This project re-engineers and redesigns a current state-of-the-art sports car subframe with a target of reducing its mass by over 30% whilst reducing it's carbon content to less than 0.5 tons per ton.

PIVOT marks a seminal moment in casting technology.

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LEVA

Lightweight Electric Vehicle Architecture

Investigated the structural performance of castings in crash conditions by developing the world's first 'Digital Twin' from CAE stress software models, predicting localised, post cast material structural properties and mapping them onto downstream CAE models, for use in subsequent LS-DYNA studies, and validating against physical tests.

The use of casting simulation tools to simulate the casting process and predict post cast properties has enormous benefits. It allows the casting supplier to develop the casting tool design and to assess casting and tool modifications simulating the effects of changes to the post cast heat treatment process.

Giving designers optimal structural properties for their component designs.

Foundry 2030

Foundry 2030 is another grant funded research program examining the viability of traditional castings in aerospace, particularly improved mechanical strength, increased design freedom and low buy to fly ratios.

Working alongside BCAST, the Advanced Manufacturing Research Centre (AMRC), and the Aerospace Technology Institute (ATI) work focussed on a wing roller (image opposite) from a major European plane manufacturer: the side bars were topologically optimised for lighter weight.

Foundry 2030 demonstrated that Low Pressure die casting and digital simulations can cast safety critical aero-structural components with 30% weight savings, ~95% buy-to-fly ratios, and have similar property variance (<3.5% UTS, <4% yield strength) to wrought metal; with the capability to utilise secondary aluminium.

Traditional castings will transform aerospace component costs.

LEAST

Lightweight Energy Absorbing Structures for Transport.

Researching the development of lighter crash management systems in association with the UK's largest automotive manufacturer and Brunel University. This project sought to examine the potential of high energy absorption systems utilising overcasting and metal foams.

The proposal aimed to achieve a cost-effective manufacturing technology, delivering a step-change in weight reduction for crash management systems in the automotive sector. The program used a novel overcasting technology, eliminating the need for welding by using flow forming technology, to provide near net shape manufacture of components for crash management systems.

The platform for Sarginsons future development.

IRIFIO

Intelligent Robotic Inspection for Foundation Industry Optimisation

Investigating the use of Intelligent Robotic Inspection, with 3D vision and sensor technology, for automatic fault detection and the creation of datasets, to inform machine learning, so as to enhance production efficiency whilst reducing energy costs, CO2 emissions and scrap.

Current manufacturing methods are inflexible, requiring time-intensive pre-programming or manual intervention in responding to unexpected occurrences or production errors. This reduces the ability to respond to the demands of environmental targets, restricting manufacturing improvements until the production methods are updated.

World leading scanning technology for defect detection in castings.