One of the world’s leading Internet of Things (IoT) specialists has signed a deal with the Materials Processing Institute to play a crucial role in a £10m project that will explore how digital technologies can be implemented in brownfield manufacturing sites.
PTC will work with the Tees-based research and innovation centre to implement its ThingWorx Industrial Internet of Things (IIoT) platform at three steel plants across the region.
The Materials Processing Institute supports industry through the development, and commercialisation of technology for the challenges of advanced materials, industrial decarbonisation, the circular economy and digital technologies.
For this work, the institute will undertake an initial pilot project using its Normanton Steel Plant to assess and improve the Industry 4.0 technology, before applying it to production processes operated by Liberty Steel Group’s Hartlepool Pipes Mill and Stocksbridge plant.
The IIoT capability will capture and analyse data in real time, giving operators critical information that can be used to help them make changes to processes that has the potential to save tens of millions of pounds every year.
David Grammer, general manager for UK and Ireland at PTC, commented: “Digital technologies are commonplace in new build, modern factories, but implementation in older plants in more traditional sectors is a lot more difficult.
“This is why this £10m digitisation project with the Materials Processing Institute is so important for UK industry and we are delighted that ThingWorx has been chosen to help it execute a critical element of the work.
“Our experts have been working with specialists at the Institute to trial our platform over a four-week period and have made some specific changes to the software to make sure it will deliver what is required in what will be very demanding environments.”
The two-year project, which is worth £2m to the institute, is being funded by Innovate UK, the UK’s innovation agency, through its Manufacturing Made Smarter challenge, part of the government’s larger Industrial Strategy Challenge Fund.
It will focus on using camera and imaging technologies in conjunction with intelligent processing and machine learning to increase accuracy – including process characterisation, the creation of digital twins and intelligent interactive process models.
Chris Oswin, who leads the institute’s Digital Technologies Group, added his support: “We looked at a number of IIoT platforms, but it became clear relatively quickly that ThingWorx was the standout option for the project because of its ease of use, the connectivity and the way it clearly delivers actionable data in real time.
“The support from PTC experts was also impressive, listening to our specific requirements and understanding how they could adapt their technology quickly and in a way that would make implementation a lot easier.”
He continued: “Whilst this project is centred on the metals sector, it can easily be applied to any process where digital imaging can be linked to machine learning and intelligent process control.
“The three sites involved will act as demonstrators for industrial digital technologies – enabling the lessons learned to be shared across other foundation industries, including energy, oil and gas, pharmaceuticals, chemicals and the process industries.”
PTC, which has its UK base in Farnborough, has a proven track record of working with research and innovation centres, having already supported the Advanced Manufacturing Research Centre (AMRC) in Sheffield and the National Institute for Bioprocessing Research and Training in Dublin.
Whilst ThingWorx is the initial deployment, the company is already in discussion with the Institute about the benefit of cloud technology and using augmented reality (AR) to cascade vital skills throughout the workforce.
David concluded: “Vuforia Expert Capture could be a great way of training and upskilling staff by recording the expertise of a seasoned professional and sharing it via wearable tech at the heart of a steel plant.
“The same technology could also be used to solve problems quickly. For instance, when you are on the casting line, it can be very difficult to isolate and rectify an issue quickly enough to make a difference. Once a solution is found, it can be stored and using AR deployed quickly.”