By Joseph Reffitt, Deputy Chief Engineer – Digital
AI is often described as the future of engineering - a way to design faster, build smarter, cut cost, and reduce waste. The potential is huge. But it can be difficult to find examples of it working in real manufacturing.
That’s not because engineers don’t want to use AI. Faced with pressure on cost, time-to-market, and sustainability, we need every tool we can get. The real challenge is that AI only delivers when it’s built on the deep process knowledge that human engineers already have - and that’s not something an algorithm can learn from a website.
At NCC, we’re working to bridge that gap.
Where AI can make a difference
Take liquid resin infusion - a core manufacturing process for high-performance composite parts in aerospace and energy. It’s complex, costly, and still heavily reliant on experience.
Our teams are developing machine-learning models, trained on thousands of simulated infusions, to teach AI how to control the live infusion process and produce consistent quality parts. We’ve built a dedicated software environment for this, so that AI can be comprehensively trained before being applied to a real production process.
The goal isn’t to replace engineers - it’s to give them better insight and reduce rework and waste. It takes time, investment and expertise, but the prize is real - more consistent products, produced more efficiently, here in the UK.
The Data Challenge
To make AI truly useful, digital and physical processes must be able to speak the same language.
Through the High Value Manufacturing Catapult’s Model-Based Enterprise programme, NCC is helping define a common digital “source of truth” for design and production data. Today, most systems across the product lifecycle don’t talk to each other: different formats, software, and standards block progress.
Our engineers are leading work to make those systems interoperable, helping teams work better together and creating the large, structured datasets that AI tools need to function . It’s not glamorous work, but it’s essential if the UK wants to lead in AI-enabled manufacturing.
When AI Isn’t the Answer
Not every challenge needs artificial intelligence to solve it.
In the Manufacturing Energy Toolkit project, we helped UK SMEs install energy-monitoring sensors into their production lines. That simple step gave them real-time data on energy use - reducing costs, improving efficiency, and cutting waste .
No AI required.
It’s a reminder that digital transformation doesn’t always mean advanced algorithms. Often, the biggest gains come from adopting proven tools already available and using them appropriately.
At NCC, we’ve taken that learning further. Our own IoT energy-monitoring platform now ingests and standardises data from across our facility, helping us and our partners make informed decisions on performance and sustainability.
It’s not labelled “AI”, but it’s exactly the kind of practical digital innovation UK manufacturing needs.
Looking Ahead
AI will change the way we design and make products. But it won’t happen by accident.
Our focus is on use cases that deliver the greatest benefit for UK industry - and that can genuinely work in production. On resin infusion, we’re progressing fast. On data interoperability, we’re helping to unblock the system for everyone.
And through our government-funded, not-for-profit programmes, we’re providing honest, evidence-based advice - helping UK manufacturers see where AI can help, and where it can’t, yet.
If you want to talk about what’s realistic, and what’s next, get in touch.