Public Funding for Authentise Ltd

The classical design and manufacturing paradigm in aerospace leads to a high buy-to-fly ratio because almost 90% of raw materials are turned into scrap, through subtractive machining from forged billet. This is the case even for costly, advanced engineering Ti-alloys where traditional manufacturing routes are employed. Scrapping most of the raw material through machining and other processing routines also results in increased lead times which falls behind the complex requirements of the current aerospace manufacturing landscape. The DISTOPIA project will address these problem - distorting aerospace manufacturing boundaries - by developing an automated, cost-efficient wire-fed DED additive manufacturing (AM) and repairing method, made possible using novel metallic wires with enhanced mechanical properties; combined with implementation of a full digital twin model of the process. Additive manufacturing (AM) provides an alternative perspective compared to the conventional methods, particularly regarding the utilisation of raw materials, complex design capabilities, decreased lead times and costs as a combined effect. Wire-fed DED, commonly referred to as WAAM, is one of the AM techniques which ensures a high rate of productivity by leveraging arc welding while also maintaining reasonable costs through the use of traditional equipment like industrial robots and welding sources. DISTOPIA focuses on a critical aspect for the future of WAAM, as current trend on AM is development of new materials that offer superior productivity and material properties compared to the ones developed and optimised for conventional manufacturing routes. This, combined with the use of advanced process monitoring and control systems will lead the way for the optimisation and adaptation of the technology for the aerospace industry. These will overcome critical barriers to entry for the WAAM DED approach, helping to make the approach more readily available and accepted. Cost will be significantly reduced in two main ways: 1. By requiring only wire material as needed for part mass 2. By eliminating the requirement for stock - typically over 2 million spare parts across multiple aircraft designs. These savings will increase the global competitiveness of the European aerospace industry and support sustainable development goals. With DISTOPIA this will be demonstrated for 3 aerospace manufacturing/repair examples, as well as considering applicability to other sectors (mining, energy, chemical processing).

In LEAD (Low Energy Autonomous Digital) Factory we have put together a consortium containing the world's leading companies in their relevant disciplines, combining their innovation strengths to allow us to create a new method of manufacturing. This unique process will create functional plastics from plant waste, converting them into usable, functional polymers. The manufacturing process using these polymers will then not only be low energy during manufacture but be clean with no harmful emissions in gas or liquid effluent. It will be entirely controlled digitally from the creation of the object and also right through its operation. To ensure circularity in the process we have developed an innovative recovery process to gain useful elements back from the plastic at end of life. Creating parts digitally has numerous energy, productivity, and waste reduction benefits; the parts can be optimised to a greater extent as tooling is always a compromise created from the need to launch rapidly while avoiding expensive tooling modifications, there is no carbon in the tool and product can be supplied immediately in the quantity required, made near the point of need. This offers the potential of being a disruptive game-changing alternative to injection moulding. This project will design, assemble and validate a novel production line powered by 3D printers and validate its capabilities by manufacturing six very different products: glasses, figurines, electronic components, auto parts, lamp shades and dental aligners. These will be validated by leading companies in their fields. We will calculate CO2 savings for them and then be able to extrapolate these savings if widely applied to supply plastic within the UK. This project can act as a trigger for starting the next digital industrial revolution of manufacturing, again here in the UK.

Metals production, from mining ore through manufacturing parts, accounts for 7% of global energy use. While metal additive manufacturing (AM) has been promoted as a way to help us reduce our carbon footprint, this has not been well demonstrated with clear and complete information. Furthermore, there lacks a comprehensive comparison of energy consumption by the different AM processes. To optimize when, where, which, and how to implement AM, we must be able to assess its environmental impact and compare this to conventional manufacturing processes like CNC Machining. For effective analysis, we must consider the whole manufacturing lifecycle. This includes all the steps from feedstock manufacturing, printing, post-processing, and any material reuse along the way. Continuing studies and analysis will only achieve so much, the need to implement digital tools that can monitor, analyse, predict and alert a range of impact and deviations in standard operating procedures is fundamental to continue the maturing of a manufacturing process which has already had an impact on material efficiency. The process of AM is sensitive to many factors, and while AM opens many design efficiencies, such as part consolidation, the energy impact from materials requiring conditioning, not meeting required standards and the time taken to develop build parameters to ensure build by build stability is key to reducing energy use. A print failure has tremendous energy impact. A CNC machine will use 23 KWh per Kg of material removed, with a high rate of success in part quality. Compared to AM and L-PBF which uses on average 80.5 KWh per Kg of material added. Part acceptance rates for L-PBF are lower than a CNC Machine. For every 100kg of material processed, assuming an equal 10% part-failure rate, 805 KWh of energy would be wasted versus the 230KWh for CNC. The development of the tools proposed within the SAMCRD project would make a profound impact in energy reduction and accelerate additive manufacturing as a viable sustainable production process as part of the UK's manufacturing capabilities.

The aim of the "Digital Supply Chain Adoption Curve" - DSCAC - project is to provide a product roadmap that helps deliver the vision of a fully integrated, digital supply chain. While the vision is not new, it has been stifled by a lack of adoption. That's despite the fact that such an integration could deliver significant value in terms of efficiency, agility and security.- Yet, the vision has been held back by the fact that tools don't address needs and fears of supply chain participants, particularly SME's. Challenges include, among others, (a) companies fears related to sharing intellectual property, as well as (b) the inadequacy of digital tools, particularly at SME level, and the related necessity. Through its previous work on both connected Manufacturing Execution Systems and research related to light weight digital supply chain tools, Authentise discovered a myriad of opportunities potentially exist that deliver value but, in falling short of full integration, address some of the challenges that have prevented this full integration from occurring. Intermediate products that address a particular need while limiting the information requirement, the adoption of a fully digital supply chain can be sped up. It is important that these tools are considered holistically to ensure that they are contributing to the vision of a fully integrated supply chain. Thus, in this feasibility study the main aim is to learn (including reviewing existing solutions and literature and questioning key supply chain stakeholders), design (including identifying potential product areas - both served and unserved - and compiling full product definitions on each of them), and test (including high level test with industry interviews and granular test in the TWI test bed) an integrated digital supply chain. The result is not just a report but a full set of product definitions that industry participants can use to identify and de-risk potential market opportunities. This type of holistic review yielding a product roadmap has not been available previously. The combination of research organisations (JI4C, TWI) with a software vendor (Authentise) and a certification agency (Lloyd's Register) will ensure that these solutions have both regulatory and academic rigor whilst maintaining an action oriented approach that software vendors can use to deliver real-world results, which may be pursued through a follow on Industrial Research application.

The global emergence of COVID-19 has underscored the need for a reliable supply of respiratory facial protection which, if used correctly, it can provide adequate protection from the infection for all users, from healthcare workers to medically vulnerable individuals. Currently, the vast majority of respiratory facial protection includes masks that are disposable and standard-fit, not tailored to an individual's face. We have identified the critical need for supply of reusable masks that are custom-fitted. This need arises from the primarily from around 150,000 NHS workers who are struggling to have their masks adequately fitted and therefore unable to safely protect themselves in the clinical environment. Additionally, the environmental impact of disposable masks is enormous, with \>400,000,000 masks being distributed by the NHS in 4.5 months. This project aims to combat both the fit issue and the environmental impact of disposable masks by creating a prototype of a reusable mask which is custom-fitted to an individual and meets the necessary regulatory and safety standards. Our innovative project aims to develop a facial scanning app that users can access from their own mobile device. The relevant data will be then transmitted through our platform resulting in the production of a reusable custom-fitted mask.