The Data Lab, Scotland’s centre for data and artificial intelligence, played a key role in delivering the £53.8 million Smart Manufacturing Data Hub (SMDH), which supported businesses in adopting new digital tools.

Despite the potential of technologies like AI and machine learning, small and medium-sized manufacturing firms struggle to adopt them because of financial, technical and practical challenges in changing how they work.

The SMDH programme helped tackle these challenges by providing expert support and funding.

Some 320 firms across the UK, including 140 in Scotland, took part in more than 200 projects tackling machine efficiency, energy waste and supply chain disruption.

The Data Lab led the Scottish projects within the three-year programme, attracting over £4 million of co-investment to boost innovation across the country.

Grant funding enabled manufacturers to work with experts, train staff and adopt new data tools and technologies.

The projects cut energy costs by an average of 28%, saving £183,000 in total.

CO2 emissions fell by around 30%, equal to 162 tonnes saved. Wasted energy dropped by 22%, saving 656,744 kilowatt hours.

Led by Ulster University, the SMDH is the largest consortium The Data Lab has been part of in its 11-year history.

The Data Lab led a team of 18 data scientists, many of them recent graduates, who worked with industry and partners to bring 40 new tools to market and support the launch of 16 spin-outs and start-ups.

It also created an online community of more than 400 members from manufacturing firms across the UK and beyond, enabling them to share and access data tools designed to cut emissions, reduce waste and boost productivity.

The hub supported more than 4,000 people to gain new skills, helping embed data science across the manufacturing sector.

Adam Turner, who led the SMDH programme in Scotland and is head of external funding at The Data Lab, said: “Manufacturers often don’t think of themselves as data-rich, but when we speak to teams on the factory floor, they’re amazed by the wealth of information they already have.

“From food and drink to the energy sector, we’ve helped companies unlock the value in that data through practical solutions built by our team of data scientists.

“That includes tools like our energy insights platform, which helps firms understand the types of energy they’re using and where they can cut back, and systems that identify how efficiently their machines are running.

“These solutions are helping businesses save money, cut emissions and improve performance.

“We’ve helped companies turn a page in understanding the true value of data.

One such company is Stewart-Buchanan Gauges in Kilsyth, North Lanarkshire.

The firm received a small business grant along with support to trial new equipment that monitored energy use across several machines.

Data scientists from The Data Lab helped analyse the energy draw and identify where the company could reduce costs.

IT manager Jim Boyle said: “When I started, we had no data capture from any of the factory machines.

“Thanks to SMDH, all the machines now have their own monitoring solutions and dashboards, and since we’ve started monitoring them, we’ve noticed a drop in the bills.

“So it’s saving us money, and in an employee-owned business that money goes straight back to the staff.

“Understanding all this data will help us know where we make our money. This is how we safeguard this business’s future.”

The programme formed part of the £300 million Made Smarter Innovation Challenge – a UK government and industry partnership aimed at accelerating the development and adoption of digital technologies across manufacturing.

Alongside The Data Lab and Ulster University, SMDH partners included the University of Cambridge, the University of Dundee, Energy Systems Catapult, Manufacturing Northern Ireland, Scottish Engineering, the Manufacturing and Engineering Growth Advancement Network, Institute for Manufacturing, Industry Wales, D2N2 Local Enterprise Partnership and the Science and Technology Facilities Council.