“Our products create massive amounts of data throughout their entire lifecycle, bringing this data together requires a new set of skills, no blueprint exists yet because the ways of working have changed significantly.”

Dave Holmes
Operations & Technology Director, BAE Systems​

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Use cases

Wind Tunnel Testing​

By simulating an aircraft using computational methods such as Computational Fluid Dynamics (CFD), engineers can mimic the physical domain and run virtual wind tunnel experiments for a fraction of the price. This allows aerospace engineers to understand the performance of designs in advance, thus narrowing down the right design choices for the prototype stage.
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Flight dynamics

Predict turbulent aircraft behavior with Monolith. ​Perform dynamics tests in 72–80% less time using Bayesian Deep Learning in a clever new way. As gusts occur at many different winds speeds, flight altitudes, and for differently loaded aircraft, engineers need to manually check 1000s of scenarios – a tremendously complicated task.​
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Key Aerospace and Defense industry challenges

1.

Knowledge retention is becoming harder, as engineers rarely remain at a company for the entire product lifecycle. As such, data-driven processes are the key to product knowledge and continuity.

2.

The aerospace industry is committed to carbon neutrality, but product testing within the aerospace industry is extremely harmful to that goal. Data-driven modeling enables the reduction of physical testing and makes it easier to achieve carbon neutrality.

3.

The aerospace industry generates huge amounts of data, but this data is costly and hard to process in a meaningful way.​

Data in Engineering | Rolls Royce & Monolith

Rolls Royce CDO discusses data in engineering, and why Monolith has proven to be the ultimate solution.