University of Nottingham
Canvas Category Consultancy : Research : Academic
The Institute for Advanced Manufacturing (IfAM) encompasses a multidisciplinary team of established academics in their respective fields in the UK and at our campuses in Malaysia and China. This provides the foundation needed for research and world-leading facilities to encourage the development of new technologies and systems for production of high-value products within the manufacturing sector. IfAM is dedicated to supporting UK manufacturing to revitalise the British economy through innovation and collaboration.
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Uni spin-out secures £340,000 investment to transform efficiency of electric vehicles and accelerate journey to NetZero with groundbreaking power electronics
University of Nottingham spin-out, The Thinking Pod innovations (TTPi), has secured £340,000 in its first investment round to commercialise pioneering power electronics technology, which reduce the environmental impact and cost of electric vehicles. TTPi has developed groundbreaking technology in collaboration with the University of Nottingham, which will boost the efficiency and range of electric cars.
The company was founded in 2017 and to date, the firm has been funded through grants from Innovate UK, UKRI, Driving the Electric Revolution and income generated from commercial development agreements with partners such as Advanced Electric Machines, National Grid ESO and Infineon Technologies.
TTPi’s novel technology enables the creation of smaller, lighter, more efficient power converters and motor drive systems, which are essential in electric vehicles, aircraft, and any dynamic industrial processes that rely on electricity as a power source.
TTPi’s converters are lighter than existing products and are currently in prototype testing. TTPi is now working towards Technology Readiness Level (TRL) 6 and samples will be available for third-party testing in Q2 2025. The company plans to undertake a second investment round late next year.
Promethean Particles Announces Closure of £8M Series A Investment Round
Promethean Particles announces the closing of a £8 million financing round. The investment was led by Mercia Ventures and Aramco Ventures, with participation from existing investors including the Midlands Engine Investment Fund I (managed by Foresight), the University of Nottingham, TSP Ventures, and the East Midlands Early Growth Fund (managed by the British Business Bank).
MOFs are a class of materials composed of metal ions interconnected by organic molecules to form a porous, lattice-like structure. Their unique architecture gives them an exceptionally high surface area and customizable pore sizes, which allows them to trap and store gases and liquids efficiently. This makes MOFs highly effective for applications such as gas storage and separation, carbon capture, and catalysis.
The company has developed a proprietary continuous-flow reactor that not only dramatically improves the throughput and cost of MOF production, but also increases process reliability and consistency, without sacrificing critical quality parameters. Promethean currently produces a wide portfolio of MOFs for various customer applications including carbon capture and storage (CCS), biogas upgrading, water harvesting and gas separation and storage.
A new way to decarbonise steelmaking - BioIron
BioIron™ uses raw biomass and microwave energy instead of coal to convert Pilbara iron ore to iron and has the potential to support low carbon dioxide (CO2) steelmaking. Our modelling shows that when combined with renewable energy and carbon-circulation by fast-growing biomass, BioIron™ has the potential to reduce CO2 emissions by up to 95% compared with the current blast furnace method.
We have proven the process works at a small-scale pilot plant, and now we’re planning to test it on a larger scale at our new BioIron™ Research & Development Facility. The development of the BioIron Research and Development Facility in the Rockingham Strategic Industrial Area, south of Perth, follows successful trials of the innovative ironmaking process in a small-scale pilot plant in Germany.
The BioIron facility will include a pilot plant that will be ten times bigger than its predecessor in Germany. It will also be the first time the innovative steelmaking process has been tested at a semi-industrial scale, capable of producing one tonne of direct reduced iron per hour. It will provide the required data to assess further scaling of the technology to a larger demonstration plant.
The plant has been designed in collaboration with University of Nottingham, Metso Corporation and Western Australian engineering company Sedgman Onyx. Fabrication of the equipment will begin this year, with commissioning expected in 2026. These works are expected to support up to 60 construction jobs.
A maturity model for the autonomy of manufacturing systems
Modern manufacturing has to cope with dynamic and changing circumstances. Market fluctuations, the effects caused by unpredictable material shortages, highly variable product demand, and worker availability all require system robustness, flexibility, and resilience. To adapt to these new requirements, manufacturers should consider investigating, investing in, and implementing system autonomy. Autonomy is being adopted in multiple industrial contexts, but divergences arise when formalizing the concept of autonomous systems. To develop an implementation of autonomous manufacturing systems, it is essential to specify what autonomy means, how autonomous manufacturing systems are different from other autonomous systems, and how autonomous manufacturing systems are identified and achieved through the main features and enabling technologies. With a comprehensive literature review, this paper provides a definition of autonomy in the manufacturing context, infers the features of autonomy from different engineering domains, and presents a five-level model of autonomy — associated with maturity levels for the features — to ensure the complete identification and evaluation of autonomous manufacturing systems. The paper also presents the evaluation of a real autonomous system that serves as a use-case and a validation of the model.