Armoured Vehicle Design Optimisation Project

Armoured Vehicle Design Optimisation Project

About the Project

We were approached by a leading metals fabrication client to support them in an armoured vehicle design optimisation project.  Our client had been tasked to develop and manufacture a range of bespoke turrets and armour options to fit an existing armoured vehicle.

The project created a cost-effective way to upgrade existing military hardware; extending the life, efficiency and protection of the vehicles. It also provides the option for countries to improve their defensive capabilities by either upgrading their existing hardware or purchasing vehicles that have been already upgraded.

The Challenge

Firstly, we contacted our sister company, PES Scanning to use their 3D optical scanning services to capture details of the Spartan Armoured Personnel Carrier (APC). The scan data was captured in the form of a polygon mesh, before the data was transferred into CAD software by the design engineers. This was an essential step within the process as there was no existing CAD/digital data to utilise for design optimisation.

Reverse Engineering and Optimisation

Once the design engineers had converted the scan data into a usable CAD format, the team utilised the data to design a range of ‘bolt-ons’ that would be manufactured to the designed specification, in order to fit the specific test vehicle perfectly. Many vehicles may have been modernised and upgraded a number of times during their operational lifetime. Capturing the data relevant to a specific vehicle allowed the team to guarantee that the new bespoke design would fit the vehicle.

The scan data was not only used for reverse engineering the fit of new equipment, it was also used for space claim.  This ensured that any new designs would operate unhindered on the hull, clearing any equipment or crew positions. The digital information is also compatible with computational fluid dynamics (CFD) or finite element analysis (FEA) software and allows virtual simulations to be run. In this case the new upgrades could be analysed virtually to ensure that they delivered the required performance before the first physical prototypes are manufactured.

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