Manufacturing in the UK is undergoing significant transitions and transformations in terms of new emerging technologies and methods. The traditional view of using a range of disparate processes in a precisely defined logical sequence of steps is now being challenged by the continued emergence and growth of metal additive layer technologies, most commonly termed additive manufacturing. With projected growth in this sector increasing (current annual compound growth rate is 34.9%), it's continued involvement in manufacturing is set to increase considerably. However, the major bottleneck is the significant additional finishing processes required after initial generation of the component. The streamlined and integrated combination of AM and subtractive process is now being termed hybrid manufacture. Current design for manufacture methods are well-established techniques that allow designs to be adapted to enable efficient production using traditional linear manufacturing approaches. However these current state of the art methods are not directly applicable to new emerging manufacturing techniques, without significant modification and adaption. This will impede the generation and uptake of novel and emerging manufacturing processes, further stagnating design. Project DHarMa (Design for Hybrid Manufacture) aims to deliver a disruptive, design rationale and process that is specifically targeted at enhanced utilisation of combined additive and subtractive technologies in the form of hybrid manufacture (HM). This will be achieved by undertaking systematic, quantitative and qualitative research that will focus on generating a design for hybrid manufacturing process, based on identified design features and geometry classifications in seamless conjunction with hybrid manufacturing key performance indices and a manufacturing capability framework. DHarMa will incorporate specific additive and subtractive manufacturing information constructs in conjunction with design feature and geometry relationships and attributes. Essentially this will integrate and categorise part specific design and manufacturing information and will be used to generate the DHarMa process. Designers will have a powerful tool that will enable them to tailor and adapt their designs to be manufactured using a combination of additive and subtractive technologies. Unlike conventional manufacturing that has significant limitations in terms of features and geometries that can be correctly generated, AM un-constrains manufacturing with the direct capability to create highly complex features and geometries that would be typically inaccessible using conventional methods (for example, dematerialised internal thin walled features). This affords the designer more design freedom and flexibility, thus empowering them to create new innovative products without the need to be constrained by a rigid set of conventional manufacturing protocols. This feasibility project will provide the initial study in to the generation of a design process that will enable parts to be specifically designed for manufacture using a HM approach. This will initially be based on prismatic designs that will be applied to HM.

Climate change is the most pressing environmental challenge of our time. The transport sector was the largest contributor to UK greenhouse gas emissions (GHG) in 2020, with an overall contribution of 24% [1]. While decarbonisation of on-road transportation, such as cars, buses and trucks, is well underway by employing electric alternatives, the important sector of off-road vehicles is technologically far behind and represents a major contributor to GHG emissions. In 2018, the total GHGs emission of UK off-road vehicles was 11,043 kilotonnes [2], which is equivalent to the GHGs emission from 12.2 Giga pounds of coal burned, or the annual energy use of 1.4m homes' [3]. Hydraulic fluid power transmission is widely used in off-road vehicles, such as construction and agricultural machinery. Current state-of-the-art hydraulic fluid power components and control technologies continue to be highly energy- and cost-inefficient and generate significant CO2 emissions, as speed and force are controlled by using metering valves to throttle the flow and control the hydraulic pressure. This is a simple but extremely inefficient method because the energy is dissipated through an orifice and consequently lost as heat; it is common for more than 50% of the input power to be wasted in this way. A recent study showed that the average energy power efficiency of fluid power systems is only 21%, and a 5% improvement in efficiency can save 0.51 quadrillion Btu of energy, which relates to a saving of US$10.1 billion and a reduction in CO2 emissions of over 33.95 million tonnes. Therefore, there is an urgent need to create new technologies to significantly improve hydraulic energy efficiency to enable efficient decarbonisation and electrification of off-road vehicles and achieve Net Zero. To significantly improve hydraulic fluid power efficiency to over 90%, I will provide a transformative change in next-generation digital hydraulic components and control technologies by developing new additively manufactured high-performance digital hydraulic valves (WP1) and novel digital hydraulic converters (WP2) to reduce hydraulic pressure and energy losses. I will create high-fidelity analytical modelling tools to understand the underlying science of complex fluid power components and systems and establish new additive manufacturing-based designs and methodologies for energy-efficient digital valves and converters. An intelligent control platform (WP3) which will integrate model- and machine-learning-based control algorithms, will be developed to control the digital valves and converters to achieve their optimum performance and maximum efficiencies. These transformative and emerging technologies will be implemented on off-road vehicles (e.g. excavators, elevating platforms) as technology demonstrations and case studies (WP4) in order to produce future digital hydraulic fluid power products and solutions for Net Zero (WP5). I will conduct scoping studies in Phases 1 and 2 to define new research directions, deliver high-impact publications and conduct the pathways to impact activities. The research outcomes will generate significant academic, economic and societal impact. They will ensure the UK has a unique world-leading research activity in digital fluid power and its future applications. UK-based companies will receive a competitive advantage in exploiting the deliverables from the Fellowship and in significantly influencing the application potential of digital hydraulic fluid power in the market, which can have an immense range of customers. The research outcomes will provide long-term zero-carbon machines for people living and improving their quality of life. [1]. 2020 UK Greenhouse Gas Emissions, Final Figures. National Statistics. Department for Business, Energy & Industrial Strategy. 2022. [2]. National Atmospheric Emissions Inventory UK Data. 2022. [3]. Greenhouse Gas Equivalencies Calculator, the US Environmental Protection Agency. 2022.

Additive manufacture, also known as 3D printing, offers many benefits to industry and medicine such as reductions in weight, material costs and medical implants personalised to the patient. Currently additive manufacture has a relatively low uptake due to a series of technical barriers that are preventing its progression into end-use parts. One of these barriers is design. Design for additive manufacture (DfAM) requires the engineer to think in a different way, one that is the completely opposite to design for traditional manufacturing methods such as milling. Similarly, the majority of software on the market is computer aided design (CAD) which has been developed to support the design of parts using traditional manufacturing methods. This research approaches this challenge, from a radically different perspective. Growth in animals and plants involves the expansion and multiplication of cells, to incrementally increase the volume of the form. In this way additive manufacture, which bonds material point by point, is analogous to growth. Two novel design techniques will be developed in this project. They are drawn from concepts seen in the development of the fetus and the plant root, and integrated into a software called GrowCAD. The development of GrowCAD will create a software interface which is more intuitive to DfAM. The platform will also incorporate Temporal Design, which will increase creativity in the design of additively manufactured materials. The design approaches will be confirmed against the AM and testing of biomaterials for cardiovascular implants and three industrial applications proposed by the project partners. This project offers a solution to the challenges that face DfAM, across industrial and medical applications. This research offers benefits to the UK economy by increasing the uptake of additive manufacture, and the inherent upskilling of design engineers through use of the software. In addition, there will be benefits to society through increased creativity in the design of cardiovascular implants, and thus enhanced levels of personalisation in healthcare.

It is readily acknowledged that decisions made in the early design stages influence the product cost, performance, utility and impact on the environment. However, we know that advances in new technologies such as Additive Manufacturing result in compressed design and manufacturing cycles. Smart materials and automation influence the manufacturing system and the need for a data-driven manufacturing value-chain utilising the Internet of Things and Industry 4.0 changes the business models and consequently the entire manufacturing environment. Basically, to meet future manufacturing needs our design and manufacturing tools need to transcend disciplines and industrial sectors. However, as researchers we tend to focus on on multi-disciplinary engineering (where experts from various disciplines draw on each other knowledge) or inter-disciplinary (where expert knowledge, tools and methods are integrated together to solve a single challenge). It is our view that we need to create new knowledge beyond the single subject of investigation/discipline and provide methods for engineers of the future to use. Our vision is to create this capability with a pipe-line of 'Trans-Disciplinary Design-Engineers' and evolving tools to enable rapid uptake across sectors of enhanced and new manufacturing processes. To achieve our vision, the heart of our Platform proposal is focussed on the retention and development of our Early Career Research staff. To sustain and expand our talent pipeline, we are providing career management and targeted staff development. This will enable our research staff to leap forward into their next career step and become Trans-Disciplinary Design-Engineers, who have the skills to realise the potential of current and future manufacturing processes and techniques. The under-pinning research will provide these trans-disciplinary design engineers with a suite of evolving models. The models will be dynamic, data driven and will allow designers to be trans-disciplinary through providing the means to understand new manufacturing process, costs, economics and complete through life decisions at the early stages of a design. Fundamentally changing how 21st century products are designed.

The nuclear industry has some of the most extreme environments in the world, with radiation levels and other hazards frequently restricting human access to facilities. Even when human entry is possible, the risks can be significant and very low levels of productivity. To date, robotic systems have had limited impact on the nuclear industry, but it is clear that they offer considerable opportunities for improved productivity and significantly reduced human risk. The nuclear industry has a vast array of highly complex and diverse challenges that span the entire industry: decommissioning and waste management, Plant Life Extension (PLEX), Nuclear New Build (NNB), small modular reactors (SMRs) and fusion. Whilst the challenges across the nuclear industry are varied, they share many similarities that relate to the extreme conditions that are present. Vitally these similarities also translate across into other environments, such as space, oil and gas and mining, all of which, for example, have challenges associated with radiation (high energy cosmic rays in space and the presence of naturally occurring radioactive materials (NORM) in mining and oil and gas). Major hazards associated with the nuclear industry include radiation; storage media (for example water, air, vacuum); lack of utilities (such as lighting, power or communications); restricted access; unstructured environments. These hazards mean that some challenges are currently intractable in the absence of solutions that will rely on future capabilities in Robotics and Artificial Intelligence (RAI). Reliable robotic systems are not just essential for future operations in the nuclear industry, but they also offer the potential to transform the industry globally. In decommissioning, robots will be required to characterise facilities (e.g. map dose rates, generate topographical maps and identify materials), inspect vessels and infrastructure, move, manipulate, cut, sort and segregate waste and assist operations staff. To support the life extension of existing nuclear power plants, robotic systems will be required to inspect and assess the integrity and condition of equipment and facilities and might even be used to implement urgent repairs in hard to reach areas of the plant. Similar systems will be required in NNB, fusion reactors and SMRs. Furthermore, it is essential that past mistakes in the design of nuclear facilities, which makes the deployment of robotic systems highly challenging, do not perpetuate into future builds. Even newly constructed facilities such as CERN, which now has many areas that are inaccessible to humans because of high radioactive dose rates, has been designed for human, rather than robotic intervention. Another major challenge that RAIN will grapple with is the use of digital technologies within the nuclear sector. Virtual and Augmented Reality, AI and machine learning have arrived but the nuclear sector is poorly positioned to understand and use these rapidly emerging technologies. RAIN will deliver the necessary step changes in fundamental robotics science and establish the pathways to impact that will enable the creation of a research and innovation ecosystem with the capability to lead the world in nuclear robotics. While our centre of gravity is around nuclear we have a keen focus on applications and exploitation in a much wider range of challenging environments.