Digital Manufacturing relies on pervasive and ubiquitous use of Information and Communication Technology (ICT), sensors, intelligent robots to deliver the next generation of intelligent, co-operating and interconnected manufacturing systems. The research is aimed to improve techniques that can be used to develop digitalised manufacturing systems to reduce existing inefficiencies in production processes that impact on production costs, unplanned downtime, quality and yields. This is not only detrimental to manufacturing businesses but has a negative impact on the UK Economy. The current productivity levels of UK manufacturers and suppliers is lagging behind global competitors and prevents the UK from successfully competing with other countries in the manufacturing domain - which is vital to keep businesses and jobs in the UK rather than relocate production abroad. The UK Government wants to increase the strength of the UK Manufacturing Sector. A key means of doing this is the widespread adoption of industrial digital technologies (IDT). Cyber Manufacturing Systems (CMS) are the building blocks of digitalised manufacturing and generate vast amount of data that can be used for real time decision making to achieve optimised performance through predictive and prescriptive analytics. The latter are techniques that use, combine and analyse available data to develop computational models that can predict future outcomes and determine the best course of action.The research, under the fellowship, solves some of the existing problems in this area (CMS), developing new techniques and resources for predictive and prescriptive analytics with the potential to increase efficiency, accuracy and productivity of manufacturing processes. Businesses are therefore more likely to adopt IDTs and improve profitability and sustainability and provide high-quality jobs in a thriving part of the economy. This project will study novel and robust data analytics methods that will enable to build predictive models that take into account uncertainty, complexity and dynamic behaviour of productions systems. The project will involve: Objective 1 - develop algorithms that can reuse previously acquired data/knowledge to build more accurate predictive models that work well in the presence of noise (i.e. 'robust'), are able to adapt to changes over time (i.e. 'resilient') and can be scaled up across multiple factories (i.e. 'transferable'). Objective 2 - develop and test novel non-parametric methods for estimation of uncertainty and risks associated to a decision to enable real time mission and safety critical decision making (both automated and human driven) based on predictions. Objective 3 - iteratively develop, deploy and test predictive and prescriptive models in real and simulated industrial scenarios to obtain acceptable level of performance, usability and robustness. There will be significant involvement from industrial collaborators who will provide labelled and aggregated datasets for testing the proposed methods through computer simulations and enable feasibility studies to be conducted in factory environments. The outcomes of the research, as mentioned above, are ultimately to improve the quality of products, achieving less wastage and unnecessary costs. Through increased adoption of IDTs, the production of goods will, importantly, be more efficient, reliable and profitable. This will support the regeneration of the Manufacturing Sector and boost the global competitiveness of the UK.

The Centre's themes align with the 'Towards A Data Driven Future' and 'Enabling Intelligence' priority areas, meeting the needs identified by UKRI to provide a highly skilled - and in demand - workforce focused on ensuring positive, human-centred benefits accrued from innovations in data driven and intelligence-based systems. The Centre has a distinct and methodologically challenging "people-first" perspective: unlike an application-orientated approach (where techniques are applied to neatly or simplistically defined problems, sometimes called "solutionism"), this lens will ensure that intense, multi-faceted and iterative explorations of the needs, capabilities and values of people, and wider societal views, challenge and disrupt computational science. In a world of big data and artificial intelligence, the precious smallness of real individuals with their values and aspirations are easily overlooked. Even though the impact of data-driven approaches and intelligence are only beginning to be felt at a human scale, there are already signs of concern over what these will mean for life, with governments and others worldwide addressing implications for education, jobs, safety and indeed even what is unique in being human. Sociologists, economists and policy makers of course have a role in ensuring positive outcomes for people and society of data-driven and intelligence systems; but, computational scientists have a pivotal duty too. Our viewpoint, then, will always see the human as a first-class citizen in the future physical-digital world, not perceiving themselves as outwitted, devalued or marginalised by the expanding capabilities of machine computation, automation and communication. Swansea and the wider region of Wales is a place and community where new understandings of data science and machine intelligence are being formed within four challenging contexts defined in the Internet Coast City Deal: Life Science and Well-being; Smart Manufacturing; Smart and Sustainable Energy; and Economic Acceleration. Studies commissioned by the City Deal and BEIS evidence the science and innovation strengths in Swansea and region in these areas and indicate how transformational investments in these areas will be for the region and the UK. Our Centre will, then, immerse cohorts in these contexts to challenge them methodologically and scientifically. The use of data-driven and intelligence systems in each of the four contexts gives rise to security, privacy and wider ethical, legal, governance and regulatory issues and our Centre also has a cross-cutting theme to train students to understand, accommodate and shape current and future developments in these regards. Cohort members will work to consider how the Centre's challenge themes direct and drive their thinking about data and intelligence, benefitting from both the multidisciplinary team that have built strong research agendas and connections with each of the contexts and the rich set of stakeholders that are our Centre has assembled. Importantly, a process of pivoting between challenge themes will be applied: insights, methods and challenges from one theme and its research projects will be tested and extended in others with the aim of enriching all. These, along with several other mechanisms (such as intra- and inter-cohort sandpits and side projects) are designed to develop a powerful bonding and shaping "cohort effect". The need for and value of our Centre is evidenced by substantial external industrial investment we have have secured: £1,750,000 of cash and £4,136,050 in-kind (total:£5,886,050). These partners and stakeholders have helped create the vision and detail of the proposal and include: Vint Cerf ("father of the internet" and Vice President of Google); NHS; Pfizer; Tata Steel; Ford; QinetiQ; McAfee; Ordnance Survey; Facebook; IBM; Microsoft; Fujitsu; Worshipful Company of IT Spiritual and Ethical Panel; and, Vicki Hanson (CEO, Association of Computing Machinery).