The world's manufacturing economy has been transformed by the phenomenon of globalisation, with benefits for economies of scale, operational flexibility, risk sharing and access to new markets. It has been at the cost of a loss of manufacturing and other jobs in western economies, loss of core capabilities and increased risks of disruption in the highly interconnected and interdependent global systems. The resource demands and environmental impacts of globalisation have also led to a loss of sustainability. New highly adaptable manufacturing processes and techniques capable of operating at small scales may allow a rebalancing of the manufacturing economy. They offer the possibility of a new understanding of where and how design, manufacture and services should be carried out to achieve the most appropriate mix of capability and employment possibilities in our economies but also to minimise environmental costs, to improve product specialisation to markets and to ensure resilience of provision under natural and socio-political disruption. This proposal brings together an interdisciplinary academic team to work with industry and local communities to explore the impact of this re-distribution of manufacturing (RDM) at the scale of the city and its hinterland, using Bristol as an example in its European Green Capital year, and concentrating on the issues of resilience and sustainability. The aim of this exploration will be to develop a vision, roadmap and research agenda for the implications of RDM for the city, and at the same time develop a methodology for networked collaboration between the many stakeholders that will allow deep understanding of the issues to be achieved and new approaches to their resolution explored. The network will study the issues from a number of disciplinary perspectives, bringing together experts in manufacturing, design, logistics, operations management, infrastructure, resilience, sustainability, engineering systems, geographical sciences, mathematical modelling and beyond. They will consider how RDM may contribute to the resilience and sustainability of a city in a number of ways: firstly, how can we characterise the economic, social and environmental challenges that we face in the city for which RDM may contribute to a solution? Secondly, what are the technical developments, for example in manufacturing equipment and digital technologies, that are enablers for RDM, and what are their implications for a range of manufacturing applications and for the design of products and systems? Thirdly, what are the social and political developments, for example in public policy, in regulation, in the rise of social enterprise or environmentalism that impact on RDM and what are their implications? Fourthly, what are the business implications, on supply networks and logistics arrangements, of the re-distribution? Finally, what are the implications for the physical and digital infrastructure of the city? In addition, the network will, through the way in which it carries out embedded focused studies, explore mechanisms by which interdisciplinary teams may come together to address societal grand challenges and develop research agendas for their solution. These will be based on working together using a combination of a Collaboratory - a centre without walls - and a Living Lab - a gathering of public-private partnerships in which businesses, researchers, authorities, and citizens work together for the creation of new services, business ideas, markets, and technologies.

The vision of RM4L is that, by 2022 we will have achieved a transformation in construction materials, using the biomimetic approach first adopted in M4L, to create materials that will adapt to their environment, develop immunity to harmful actions, self-diagnose the on-set of deterioration and self-heal when damaged. This innovative research into smart materials will engender a step-change in the value placed on infrastructure materials and provide a much higher level of confidence and reliability in the performance of our infrastructure systems. The ambitious programme of inter-related work is divided into four Research Themes (RTs); RT1: Self-healing of cracks at multiple scales, RT2: Self-healing of time-dependent and cyclic loading damage, RT3: Self-diagnosis and immunisation against physical damage, and RT4: Self-diagnosis and healing of chemical damage. These bring together the four complementary technology areas of self-diagnosis (SD); self-immunisation and self-healing (SH); modelling and tailoring; and scaling up to address a diverse range of applications such as cast in-situ, precast, repair systems, overlays and geotechnical systems. Each application will have a nominated 'champion' to ensure viable solutions are developed. There are multiple inter-relationships between the Themes. The nature of the proposed research will be highly varied and encompass, amongst other things, fundamental physico-chemical actions of healing systems, flaws in potentially viable SH systems; embryonic and high-risk ideas for SH and SD; and underpinning mathematical models and optimisation studies for combined self-diagnosing/self-healing/self-immunisation systems. Industry, including our industrial partners throughout the construction supply chain and those responsible for the provision, management and maintenance of the world's built environment infrastructure will be the main beneficiaries of this project. We will realise our vision by addressing applications that are directly informed by these industrial partners. By working with them across the supply chain and engaging with complementary initiatives such as UKCRIC, we will develop a suite of real life demonstration projects. We will create a network for Early Career Researchers (ECRs) in this field which will further enhance the diversity and reach of our existing UK Virtual Centre of Excellence for intelligent, self-healing construction materials. We will further exploit established relationships with the international community to maximise impact and thereby generate new initiatives in a wide range of related research areas, e.g. bioscience (bacteria); chemistry (SH agents); electrochemical science (prophylactics); computational mechanics (tailoring and modelling); material science and engineering (nano-structures, polymer composites); sensors and instrumentation and advanced manufacturing. Our intention is to exploit the momentum in outreach achieved during the M4L project and advocate our work and the wider benefits of EPRSC-funded research through events targeted at the general public and private industry. The academic impact of this research will be facilitated through open-access publications in high-impact journals and by engagement with the wider research community through interdisciplinary networks, conferences, seminars and workshops.

The traditional approach to construction is notorious for poor productivity and inadequate contribution to economic development (ONS, 2017). With the aim of boosting productivity, the construction sector must transform its methods of construction and adopt effective digital technologies (TIP, 2017). The adoption of BIM has transformed the way buildings are designed and enhanced the implementation of building manufacturing technologies such as Design for Manufacturing and Assembly (DFMA). However, the adoption of BIM by onsite frontline workers for assembly of manufactured building components is non-existent. This results in loss of the productivity gain from using BIM for design and manufacturing phases of the process (BCI, 2016). Onsite frontline workers spend more time interfacing with BIM tools than they spend on completing the actual assembly tasks. Current BIM interfaces are not practicable for onsite operations because they are too slow, hazardous and distracting for onsite frontline workers (Construction News, 2017). On this basis, the research will introduce advanced Natural Language Processing (NLP) and Conversational Artificial-Intelligence for enabling onsite frontline workers to verbally communicate with BIM systems. Assembly operations are complex and are often complicated by the uniqueness of each project, the inconsistency of assembly methods, and the diversity and alterations of project team. During onsite assembly operations, onsite frontline workers are required to quickly understand the procedure of installing building components to minimise assembly errors and reduce the overall project duration. The time spent by frontline workers can be reduced by 50% with the introduction of hands-free assembly support BIM system that utilises verbal communication. In addition to boosting productivity, it will further enhance error-free assembly operation through step-by-by assembly guide for pre-manufactured/pre-assembled building components. The development of technologies to aid easy adoption of BIM for onsite assembly has great potential to revolutionise the current approach to construction. However, apart from the slow pace and hazardous nature of current BIM interfaces, other limitations include visual obstruction, distraction and the associated health and safety challenge for frontline workers. This project aims to utilise Augmented Reality (AR) for providing visual support to access BIM systems and installation guides without obstructing or distracting the view of onsite workers. This will provide accurate and just-in-time information for online frontline workers to gradually follow the installation guide of manufactured building components. For example, an onsite assembly worker can merely ask, "hey Conversational-BIM, guide me through toilet installation" and the system will facilitate the assembly procedures through AR-assisted verbal instructions, the AR device will overlay the exact illustration of the assembly steps on the actual components onsite. It is important to note that onsite coordination between resources is vital for boosting productivity and guaranteeing faster and safer assembly (ICE, 2018). This project will therefore exploit advanced AI, computer visions, and AR technologies to develop an end-to-end BIM solution to support onsite assembly operations. In addition to boosting the productivity of frontline assembly workers, this project seeks to eliminate the tedious process of coordinating onsite activities which often involve multiple workers and machinery. Accordingly, the AR-assisted Conversational-BIM system will ensure a coordinated approach for remote experts to guide frontline workers and monitor project progress and productivity.

Globally, national infrastructure is facing significant challenges: - Ageing assets: Much of the UK's existing infrastructure is old and no longer fit for purpose. In its State of the Nation Infrastructure 2014 report the Institution of Civil Engineers stated that none of the sectors analysed were "fit for the future" and only one sector was "adequate for now". The need to future-proof existing and new infrastructure is of paramount importance and has become a constant theme in industry documents, seminars, workshops and discussions. - Increased loading: Existing infrastructure is challenged by the need to increase load and usage - be that number of passengers carried, numbers of vehicles or volume of water used - and the requirement to maintain the existing infrastructure while operating at current capacity. - Changing climate: projections for increasing numbers and severity of extreme weather events mean that our infrastructure will need to be more resilient in the future. These challenges require innovation to address them. However, in the infrastructure and construction industries tight operating margins, industry segmentation and strong emphasis on safety and reliability create barriers to introducing innovation into industry practice. CSIC is an Innovation and Knowledge Centre funded by EPSRC and Innovate UK to help address this market failure, by translating world leading research into industry implementation, working with more than 40 industry partners to develop, trial, provide and deliver high-quality, low cost, accurate sensor technologies and predictive tools which enable new ways of monitoring how infrastructure behaves during construction and asset operation, providing a whole-life approach to achieving sustainability in an integrated way. It provides training and access for industry to source, develop and deliver these new approaches to stimulate business and encourage economic growth, improving the management of the nation's infrastructure and construction industry. Our collaborative approach, bringing together leaders from industry and academia, accelerates the commercial development of emerging technologies, and promotes knowledge transfer and industry implementation to shape the future of infrastructure. Phase 2 funding will enable CSIC to address specific challenges remaining to implementation of smart infrastructure solutions. Over the next five years, to overcome these barriers and create a self-sustaining market in smart infrastructure, CSIC along with an expanded group of industry and academic partners will: - Create the complete, innovative solutions that the sector needs by integrating the components of smart infrastructure into systems approaches, bringing together sensor data and asset management decisions to improve whole life management of assets and city scale infrastructure planning; spin-in technology where necessary, to allow demonstration of smart technology in an integrated manner. - Continue to build industry confidence by working closely with partners to demonstrate and deploy new smart infrastructure solutions on live infrastructure projects. Develop projects on behalf of industry using seed-funds to fund hardware and consumables, and demonstrate capability. - Generate a compelling business case for smart infrastructure solutions together with asset owners and government organisations based on combining smarter information with whole life value models for infrastructure assets. Focus on value-driven messaging around the whole system business case for why smart infrastructure is the future, and will strive to turn today's intangibles into business drivers for the future. - Facilitate the development and expansion of the supply chain through extending our network of partners in new areas, knowledge transfer, smart infrastructure standards and influencing policy.

Infrastructure is vital for society - for economic growth and quality of life. Existing infrastructure is rapidly deteriorating, the rate of which will accelerate with increasing pressures from climate change and population growth, and the condition of the large majority of assets is unknown. Stewardship of infrastructure to ensure it continuously performs its function will be a colossal challenge for asset owners and operators. The performance of new infrastructure assets must be monitored throughout their life-cycle because they are being designed and constructed to withstand largely unknown future conditions. The UK must be better prepared to face these grand challenges by exploiting technology to increase understanding of asset deterioration and improve decision making and asset management. This research is central to EPSRC's priority area of Engineering for Sustainability and Resilience. The goal is to transform geotechnical asset management by developing new, low-cost, autonomous sensing technologies for condition appraisal and real-time communication of deterioration. This new approach will sense Acoustic Emission (AE) generated by geotechnical assets. AE is generated in soil bodies and soil-structure systems (SB&SSS) by deformation, and has been proven to propagate many tens - even hundreds - of metres along structural elements. This presents an exciting opportunity that has never been exploited before: to develop autonomous sensing systems that can be distributed across structural elements (e.g. buried pipes, pile foundations, retaining walls, tunnel linings, rail track) to listen to AE - analogous to a stethoscope being used to listen to a patient's heartbeat - and provide information on the health of infrastructure in real-time. The idea to use AE sensing to monitor geotechnical assets in this way is novel - it is expected to lead to a disruptive advance in monitoring capability and revolutionise infrastructure stewardship. AE has the potential to increase our understanding of how assets are deteriorating, which could lead to improved design approaches, and to extract more information about asset condition than existing techniques: not only deformation behaviour, but also, for example, changes in stress states, transitions from pre- to post-peak shear strength, and using correlation techniques it will be possible to locate the source of AE to target maintenance and remediation activities. AE sensing will also provide real-time warnings which will enable safety-critical decisions to be made to reduce damages and lives lost as a result of geotechnical asset failures. The number of asset monitoring locations required per unit length to achieve sufficient spatial resolution will be less than other monitoring techniques, and significantly lower cost. Piezoelectric transducers, which sense the AE, are now being developed at costs as low as a few tens of pence per sensor - this recent technological advance makes this research timely. AE sensors could be installed during construction to monitor condition throughout the life-cycle of new-build assets (e.g. HS2), and retrofitted to existing, ageing assets. This will be the most fundamental and ambitious investigation into the understanding of AE generated by SB&SSS yet attempted. The findings will mark a major leap forward in scientific understanding and our ability to exploit AE in novel asset health monitoring systems. The fellowship aims to develop robust diagnostic frameworks and analytics to interpret AE generated by geotechnical assets. This will be achieved using a powerful set of complementary element and large-scale experiments. The outcomes will be demonstrated to end-users and plans will be developed with collaborators for: full-scale field testing with in-service assets to demonstrate performance and benefits in intended applications and environments; and implementation in commercial products that could have significant societal and economic impact.