The need for more efficient, resilient, supply chains has been highlighted by various government inquiries and amplified by recent world events including Brexit and Covid-19. As organisations outsource production to one another they create economies-of-scale and reduce prices but also increase risk of disruption cascades if any member of the chain is disrupted. Typically, organisations act alone, rather than collectively, when predicting delays, disruptions and deciding on safety inventories. However, disruption data an individual organization can collect and analyse is small, imbalanced, and partial entirely to its own view. When uncertainties increase, this individualistic approach results in chaotic oscillations between stock inflation and stock-outs. Numerous studies proved that increased data sharing and collective decision making would increase resilience, but this has not been plausible as members of the chain fear that information such as capacity and excess stock can be "inferred" by clients, and used opportunistically for cost reduction. Two key emergent approaches can help change this state of affairs. First is the development of low cost platforms that facilitate data sharing for SMEs and their buyers, which we will use in this project to enable SME access to collective learning. The second is the emergence of AI technology. In this project Collective learning (CL) approaches will be developed, which will enable organizational agents to collaboratively develop a shared prediction model. Here, if one organization is able to predict a disruption, its knowledge can be shared, preventing others from stock outs. As the approach can be automated, costs of manual orchestration are avoided. CORES approaches will be integrated into low cost data integration platforms and trialled within the Aerospace sector.

The aim of this place based impact acceleration account (PBIAA) is to support the translation of University research in medical technologies into new clinical products and services. There is a vibrant Medical Technology (MedTech) business cluster in the Yorkshire region, with over 200 companies employing more than 16,000 people, mostly in high value technical roles. The Universities of Leeds and Sheffield have strong track records in engineering and physical sciences research related to MedTech, particularly in areas that mirror the local business strengths (e.g. orthopaedics, dental, implantable devices and surgical technologies). While there is clear synergy between University research strengths and the business prominence in the region, there is currently a gap in the innovation funding pathway that is preventing technology innovations developed at the region's universities from being adopted by local companies. The aim of this PBIAA is to provide support to bridge this gap and build the connections between the academic, industrial and clinical assets in the region that will help grow the regional economy. It is particularly timely because the MedTech sector is transforming and there is increasing integration of new technologies into products and services. There are growing numbers of high-growth, high-innovation MedTech companies in the region with an absorptive capacity to benefit from this PBIAA, but we will also proactively engage with established companies that need to adopt new innovations to address the changing markets. We have worked with civic partners including the West Yorkshire Combined Authority and South Yorkshire Mayoral Combined Authority, NHS Trusts through the Leeds and Sheffield Biomedical Research Centres, local industry, investors and innovation support organisations to develop this proposal and shape the activities to most effectively enable impact to be realised from the region's engineering and physical sciences research base. Commercialisation of innovations in the MedTech sector is challenging due to the regulatory barriers for products intended for use in humans, with evidence from extensive pre-clinical testing required to demonstrate the safety and efficacy. The PBIAA will fund Impact Projects that aim to generate evidence to derisk a technology, both to prove the technical concept is effective and to demonstrate that it is a commercially attractive proposition. A stage-gated approach will be used to encourage higher risk in the early stages and fast failure. These projects will act as exemplars to encourage further business engagement and outcomes will form a portfolio of evidence to inform future activities. The PBIAA will also support activities to build the regional innovation environment. These include a suite of training activities and events that raise understanding of technical advances and translational processes in the MedTech sector, and act to bring together academic, clinical and industrial partners to help build a lasting innovation community. The PBIAA will support events to identify clinical needs, two-way secondments, as well as public and patient engagement activities that aim to improve understanding of needs across the diverse regional population. A dedicated collaboration fund will be used to support impact activities at universities across the region, nurturing the wider regional strengths in this sector, and draw on wider collaborations that utilise the full strengths of the UK research base. The PBIAA will provide regional industry with a vital connection to state-of-the-art research, enabling a sustainable regional research-derived product development pipeline. It will help drive regional economic growth, with new innovations being adopted by regional industry, creating high value jobs and unlocking private sector investment in R&D, supporting a £3bn/year industry beyond 2035.

This CDT will train the next generation of manufacturing researchers with unique capabilities to combine predictive models and in-process data, with a systems perspective, to enable faster, more flexible, and more sustainable high value manufacturing. The UK's growth lags behind Europe and North America [1], and the chancellor, whilst celebrating our advanced manufacturing sector, also states [2] that 'poor productivity, skills gaps, low business investment and the over-concentration of wealth in the South-East have led to uneven and lower growth'. Although digital technologies are recognised [3] as a key productivity enabler, integrating these into an advanced manufacturing environment is a significant challenge. Our CDT will address this from a systems perspective by using sensors, communications, controls and informatics technologies that are coupled to the physics underpinning complex manufacturing processes. This vision aligns strongly with the EPSRC's priorities (especially AI Digitalisation and Data); the EPSRC Made Smarter programmes, and the UK Innovation Strategy's [4] digital and manufacturing priorities. However, embedding Digital Manufacturing into the UK economy will require people with new doctoral-level skill sets dedicated to the four productivity challenges in manufacturing: 1. sustainability - an emerging underpinning theme in our stakeholder discussions. 2. speed - reducing production lead time; 3. quality - eliminating rework whilst achieving functional performance; 4. flexibility - adaptive production systems that eliminate intrusive setup/measurement; The CDT will train cohorts that focus on cross-disciplinary research at the interface between these productivity challenges and key Digital Engineering themes identified by our industrial co-creators: (1) mechanics, modelling, and intelligent control / optimisation of processes; (2) sensor networks and monitoring; (3) manufacturing informatics, system integration, and data security. We will focus on key manufacturing processes that are essential to the UK landscape: subtractive manufacturing (machining) and product assembly. We are uniquely placed to enable this approach: we lead the machining capability on behalf of the High Value Manufacturing Catapult, collaborate on the Manufacturing Made Smarter Research Centre in Connected Factories, (with a focus on assembly automation), and through Factory 2050 we host the UK's first state of the art factory entirely dedicated to reconfigurable robotic, digitally assisted assembly and machining technologies. We will provide a unique opportunity for students to study alongside peers with a common application focus in machining, assembly, and digital engineering for manufacturing, leveraging the world leading environment provided by the Advanced Manufacturing Research Centre. This will enable the highest standards of subject-specific research training, underpinned by Sheffield's breadth of activity in engineering science. We will tailor the first year training to support their transition into the centre, and provide cohort experiences that reinforce system-level thinking and leadership skills, to ensure that our alumni's impact on society far exceeds that of a typical PhD student. Training will be undertaken individually, within a cohort, across the centre, and in combination with other centres and groups. Through this approach, we will achieve horizontal and vertical integration of the student experience within the centre and will support students in developing the specific skills required for their research. This will foster a collective culture in key training areas such as leadership, inclusion, innovation and communication, amply preparing students for their future careers. [1] IMF, World Economic Outlook Jan 2023 [2] Chancellor Jeremy Hunt's speech at Bloomberg, 27/1/2023 [3] RAEng/IET Connecting Data Report 2015 [4] UK Innovation Strategy: Leading the future by creating it