Remanufacturing is "the process of returning a used product to at least OEM original performance specification from the customers' perspective and giving the resultant product warranty that is at least equal to that of a newly manufactured equivalent". Remanufacturing can be more sustainable than manufacturing de novo "because it can be profitable and less harmful to the environment ...". Remanufacturing is a sizable industry. For example, in the USA, there are more than 73,000 companies engaged in remanufacturing. They employ 350,000 people and have turnovers totalling $53 billion. A key step in remanufacturing is disassembly of the returned product to be remanufactured. As it is complex, disassembly tends to be manually executed and is labour intensive. We propose to develop robotic technology allowing disassembly to be carried out with minimal human intervention or in a collaborative fashion by man and machine. We aim to facilitate the cost-effective robotisation of this critical step in remanufacturing to unlock the potential of remanufacturing and make it feasible for many more companies to adopt, thus helping to expand the UK's £2.35 Billion remanufacturing industry. Our research will start with a detailed investigation of disassembly processes aimed at fundamentally understanding them. Such a fundamental understanding does not currently exist but is necessary to support the development of robust disassembly strategies and systems that can autonomously handle variability in the product. We will study basic common tasks such as unscrewing, removal of pins from holes with small clearances, separation of press-fit components, extraction of elastic parts (e.g. O-rings and circlips) and breaking up of 'permanently' assembled components. We will analyse those generic disassembly tasks for feedback information that can be obtained while a robot is performing them. We will employ different types of sensors to provide feedback appropriate to a given task. In addition to visual sensing, we will focus on using contact forces and moments as a means to gauge the state of the disassembly operation. To counteract uncertainties, such feedback will be helpful in guiding the robot and avoiding damage to the components being taken apart. We will apply the acquired basic process knowledge methodically to create models, scheduling algorithms and learning tools to enable autonomous or semi-autonomous disassembly by robotic systems. We will develop strategies for planning and implementing multi-robot operation when the disassembly task is too complex for one machine. We will devise techniques for effective collaboration between humans and robots in cases where the work is too difficult for people or for machines on their own. We will validate these plans, strategies and techniques experimentally and will give public demonstrations of collaborative robotic disassembly using real products as examples. Our multi-disciplinary project team, with experience in robotic assembly, intelligent systems, CAD/CAM and process modelling, will be supported by three industrial partners (Caterpillar, Meritor and MG Motor). These user companies will supply case studies for evaluating the research results. Two technology translators (the Manufacturing Technology Centre and the High Speed Sustainable Manufacturing Institute) will contribute to converting laboratory-based technology into solutions ready for deployment on an industrial scale.

The proposed research programme will attempt to create self-reconfiguring manufacturing systems that are based on intelligent and highly accurate models of manufacturing processes and the products being manufactured. The goal of the research is to enable a radical change in manufacturing effectiveness and sustainability. The target type of manufacturing is component-based modular reconfigurable systems, i.e. systems that are built up of various elements and assembled together, in a similar fashion to building with 'lego'. This is a class of manufacturing system that is typically used in assembly and handling applications, where you tend to find families of modular machine components that can be reused and reconfigured as the product, and hence production processes change. Major applications for this are in the automotive and aerospace sectors. One example is in powertrain assembly, as seen in the UK at Ford. If the re-configurability of such production systems can be enhanced, Ford estimate that potential savings of over 30% in costs are achievable with a target of a 50% reduction in the time to build and commission such a system that typically costs £30 million per engine line. The realisation of this research has the potential to help enable the retention of high value engineering activity in the UK by improving the competiveness in the engineering of reconfigurable manufacturing systems. The capability to achieve this aim is to be built on the foundation of current, internationally leading research at Loughborough University, which has created a method for building reconfigurable systems from reusable components that is currently being adopted in automotive supply chains. The concepts of flexible and reconfigurable manufacturing systems are well established; however problems still exist in the effective, efficient, rapid, configuration of such flexible systems, particularly as lifecycle product changes occur, whether such changes are minor or more fundamental. Many flexible and reconfigurable system examples exist. However, most are designed intuitively and a systematic methodology is still lacking. Additionally, engineering this integration of product and processes is essential in a lifecycle context across the supply-chain, yet this remains largely unaddressed. Virtual engineering also has a major role to play in that we can simulate production systems and products. However the effectiveness of such simulation design tools for reconfigurable systems remains poor. Such tools need to be able to encompass the full system lifetime and be able to replicate the functions of the production system exactly in the models. These models are key enablers for understanding what might happen throughout a production system's lifecycle and can drive better configuration of the modular manufacturing systems we aspire to create.

This project will undertake the research necessary for the remote inspection and asset management of offshore wind farms and their connection to shore. This industry has the potential to be worth £2billion annually by 2025 in the UK alone according to studies for the Crown Estate. At present most Operation and Maintenance (O&M) is still undertaken manually onsite. Remote monitoring through advanced sensing, robotics, data-mining and physics-of-failure models therefore has significant potential to improve safety and reduce costs. Typically 80-90% of the cost of offshore O&M according to the Crown Estate is a function of accessibility during inspection - the need to get engineers and technicians to remote sites to evaluate a problem and decide what remedial action to undertake. Minimising the need for human intervention offshore is a key route to maximising the potential, and minimising the cost, for offshore low-carbon generation. This will also ensure potential problems are picked up early, when the intervention required is minimal, before major damage has occurred and when maintenance can be scheduled during a good weather window. As the Crown Estate has identified: "There is an increased focus on design for reliability and maintenance in the industry in general, but the reality is that there is a still a long way to go. Wind turbine, foundation and electrical elements of the project infrastructure would all benefit from innovative solutions which can demonstrably reduce O&M spending and downtime". Recent, more detailed, academic studies support this position. The wind farm is however an extremely complicated system-of-systems consisting of the wind turbines, the collection array and the connection to shore. This consists of electrical, mechanical, thermal and materials engineering systems and their complex interactions. Data needs to be extracted from each of these, assessed as to its significance and combined in models that give meaningful diagnostic and prognostic information. This needs to be achieved without overwhelming the user. Unfortunately, appropriate multi-physics sensing schemes and reliability models are a complex and developing field, and the required knowledge base is presently scattered across a variety of different UK universities and subject specialisms. This project will bring together and consolidate theoretical underpinning research from a variety of disparate prior research work, in different subject areas and at different universities. Advanced robotic monitoring and advanced sensing techniques will be integrated into diagnostic and prognostic schemes which will allow improved information to be streamed into multi-physics operational models for offshore windfarms. Life-time, reliability and physics of failure models will be adapted to provide a holistic view of wind-farms system health and include these new automated information flows. While aspects of the techniques required in this offshore application have been previously used in other fields, they are innovative for the complex problems and harsh environment in this offshore system-of-systems. 'Marinising' these methods is a substantial challenge in itself. The investigation of an integrated monitoring platform and the reformulation of models and techniques to allow synergistic use of data flow in an effective and efficient diagnostic and prognostic model is ambitious and would allow a major step change over present practice.

This Centre for Doctoral Training in Embedded Intelligence, the first in the UK, addresses high priority areas for economic growth such as autonomous complex manufactured products and systems, functional materials with high performance systems, data-to-knowledge solutions (e.g. digital healthcare and digitally connected citizens), and engineering for industry, life and health, which are also key priorities for Horizon 2020, the new EU framework programme for research and innovation. Horizon 2020 explicitly spells out ICT and Manufacturing as key industrial technologies. Its remit fits the EPSRC priority areas of ICT for Manufacturing and Data to Knowledge, and has an impact on industrial sectors as diverse as logistics, metrology, food, automotive, oil & gas, chemistry, or robotics. In addition, our world (homes, transport, workplaces, supplies of food, utilities, leisure or healthcare) is constantly seeking for interactive technologies and enhanced functionalities, and we will rely on these graduates who can translate technologies for the end-user. The uniqueness of this Centre resides on the capability to innovatively address a myriad of Embedded Intelligence challenges posed by technical needs ranging from the EI supply chain: the design stage, through manufacturing of embedded or on-bedded devices, to the software behind data collection, as well as integrative technologies, to finally the requirements from end-users. The thematic areas, discussed conjointly with industry during the preparation of this proposal, allow us also to recruit students from a vast range of educational backgrounds. A strong user pull defines the nature of the challenges that this CDT will tackle. The graduates who shall come to alleviate the shortage of skilled engineers and technologists in the field will be exposed to the following thematic areas: > Device design, specification of sensors and measurement devices (power scavenging, processing, wire & wireless communications, design for low power, condition monitoring); > Packaging & integration technologies (reliability and robustness, physical and soft integration of devices, sub-components and wider system environment); > Intelligent software (low level, embedded, system level, database integration, ontology interrogation, service oriented architectures, services design); > Manufacturing solutions (design for manufacture of embedded systems, advanced and hybrid manufacturing processes for embedding, process consolidation technologies, biomimetics and cradle-to-cradle for sustainability production, etc.); > Applications engineering (design and implementation of embedded technologies for in-time, in-line products, processes and supply chains; product and process design for embedded intelligence); > System Services: (i) Service Foundations (e.g., dynamically reconfigurable architectures, data and process integration and semantic enhanced service discovery); (ii) Service Composition (e.g. composability analyses, dynamic and adaptive processes, quality of service compositions, business driven compositions); (iii) Service Management and Monitoring (e.g. self: -configuring, -adapting, -healing, -optimising and -protecting) and (iv) Service Design and Development (e.g. engineering of business services, versioning and adaptivity, governance across supply chains). Our flagship, the 'Transition Zone' training, will facilitate the transition into doctoral studies in the first year of studies, and, closer to the end of the programme, out to industry or self-employment. As employable high calibre individuals with a good understanding of enterprising, commercialisation of research, social responsibility, gender equality and diversity, innovation management, workplaces, leadership and management, our doctorates will grow prosperity bottom up, enjoying a wealthy network of academic and industrial contacts from their years at the CDT, as well as their peers at the Centre.

The CDT proposal 'Fuel Cells and their Fuels - Clean Power for the 21st Century' is a focused and structured programme to train >52 students within 9 years in basic principles of the subject and guide them in conducting their PhD theses. This initiative answers the need for developing the human resources well before the demand for trained and experienced engineering and scientific staff begins to strongly increase towards the end of this decade. Market introduction of fuel cell products is expected from 2015 and the requirement for effort in developing robust and cost effective products will grow in parallel with market entry. The consortium consists of the Universities of Birmingham (lead), Nottingham, Loughborough, Imperial College and University College of London. Ulster University is added as a partner in developing teaching modules. The six Centre directors and the 60+ supervisor group have an excellent background of scientific and teaching expertise and are well established in national and international projects and Fuel Cell, Hydrogen and other fuel processing research and development. The Centre programme consists of seven compulsory taught modules worth 70 credit points, covering the four basic introduction modules to Fuel Cell and Hydrogen technologies and one on Safety issues, plus two business-oriented modules which were designed according to suggestions from industry partners. Further - optional - modules worth 50 credits cover the more specialised aspects of Fuel Cell and fuel processing technologies, but also include socio-economic topics and further modules on business skills that are invaluable in preparing students for their careers in industry. The programme covers the following topics out of which the individual students will select their area of specialisation: - electrochemistry, modelling, catalysis; - materials and components for low temperature fuel cells (PEFC, 80 and 120 -130 degC), and for high temperature fuel cells (SOFC) operating at 500 to 800 degC; - design, components, optimisation and control for low and high temperature fuel cell systems; including direct use of hydrocarbons in fuel cells, fuel processing and handling of fuel impurities; integration of hydrogen systems including hybrid fuel-cell-battery and gas turbine systems; optimisation, control design and modelling; integration of renewable energies into energy systems using hydrogen as a stabilising vector; - hydrogen production from fossil fuels and carbon-neutral feedstock, biological processes, and by photochemistry; hydrogen storage, and purification; development of low and high temperature electrolysers; - analysis of degradation phenomena at various scales (nano-scale in functional layers up to systems level), including the development of accelerated testing procedures; - socio-economic and cross-cutting issues: public health, public acceptance, economics, market introduction; system studies on the benefits of FCH technologies to national and international energy supply. The training programme can build on the vast investments made by the participating universities in the past and facilitated by EPSRC, EU, industry and private funds. The laboratory infrastructure is up to date and fully enables the work of the student cohort. Industry funding is used to complement the EPSRC funding and add studentships on top of the envisaged 52 placements. The Centre will emphasise the importance of networking and exchange of information across the scientific and engineering field and thus interacts strongly with the EPSRC-SUPERGEN Hub in Fuel Cells and Hydrogen, thus integrating the other UK universities active in this research area, and also encourage exchanges with other European and international training initiatives. The modules will be accessible to professionals from the interacting industry in order to foster exchange of students with their peers in industry.