Factories are learning to think for themselves. This grant funds a research platform at Loughborough University that develops machines and manufacturing systems capable of sensing their environment, adapting their behaviour, and even self-repairing without human intervention. The core challenge is that today’s industrial equipment is largely dumb: it follows fixed instructions and breaks down unpredictably. To make components that can organise, optimise, and heal themselves requires simultaneous advances in materials, wireless communications, energy harvesting, real-time software, and machine learning—a multidisciplinary problem that no single lab can solve alone. The team of 35 researchers will run “ideas factory” workshops, short feasibility studies on hot topics, and collaborative bids with industrial partners in automotive, aerospace, electronics, healthcare, and recycling sectors. If successful, this work could transform manufacturing lines from rigid, failure-prone systems into resilient, self-optimising networks that reduce downtime, cut waste, and adapt production on the fly. The grant also funds undergraduate internships and staff sabbaticals in industry to build a pipeline of UK expertise in intelligent systems—a field that underpins everything from smart factories to autonomous vehicles.
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This proposal seeks to provide a platform for strategic research and impact activities within the embedded integrated intelligent systems (EIIS) domain. This research area covers all aspects of designing and developing products and processes that can demonstrate adaptation and learning (i.e. in terms of self - organising, adapting, configuring, optimising, protecting and healing), at the system or service level based upon intelligent sensing and actuation at the granularity of the individual components. The multidisciplinary nature of the domain is challenging since successful deployment and adoption within the harsh industrial environment requires advancements in several areas (e.g. (1) materials, antennae design, embedded power sources, energy harvesting, real-time software architectures, embedded processing and robust wireless communications protocols at the device level and (2) optimisation, visualisation, analytics, machine learning and digital manufacturing at the systems science and services level). The EIIS group at Loughborough University was founded in 2007 and currently comprises 35 staff (academics (A), post doctoral research associates (PDRA) and postgraduate research students (PhD)). This proposal will enable the team to develop the EIIS strategic research agenda in line with industrial collaborators' (e.g. automotive, electronics, aerospace, sport, healthcare and end of life processing), EPSRC and Government strategies via "ideas factory" colloquia, short-term feasibility studies into "hot topics" and multi-disciplinary responsive-mode submissions to funding bodies (e.g. EPSRC, innovateUK, EU, APC/BIS, Wellcome). The funding will also support the development of a pipeline of expertise in EIIS for UK industry and academia. Undergraduates will be supported via internships in industry or academia to expose the next generation of talent to the EIIS opportunities and challenges and also provide research resource for junior members of the EIIS group. Current EIIS members will also be funded to attend technical, business and innovation courses provided by academia and / or industry and encouraged to take long term (i.e. 3 month) sabbaticals within industry and alternative world leading academic or technology transfer institutions to enable the group to identify best global practices and determine relevant benchmarks for success of the research.
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