3D printing at record scale and AI for steelmaking among tech awarded share of £14 million in funding

Project Butterfly brings together a consortium of UK manufacturing organisations, solution providers and research organisations working across a number of sectors across the UK to share best practice and demonstrate the power of I4.0 to deliver near-term impact on the road to net zero manufacturing. Small changes can have a big impact, this is known as the butterfly effect. It's this principle that Project Butterfly looks to use to accelerate progress to Net Zero. The Project has a specific focus on improving efficiency in the use of materials and energy by using manufacturing data to optimise processes, increase right-first-time yield (FTY) and provide visibility of information to everyone in the factory. This can be done by using data to automatically update the schedule to deliver the most efficient use of energy. Using data from the process to improve the process by making it more efficient or increase the right-first-time yield.

This project addresses very specific technological challenges resulting from transforming a traditional food manufacturer, still producing on machinery more than hundred-years-old, to a sustainable, optimised, and efficient enterprise fully utilising digital technologies, including Big Data, Industrial Internet of Things and Artificial Intelligence, underpinned by Food Science, to minimise its carbon footprint, maximise its capacity without compromising on its 'traditional' concept.

The project will transform the business to become a sustainable, optimised, and efficient enterprise in full control of all manufacturing processes, product consistency, supply chains, and operating costs to help the company realise new market opportunities as a result of increased production capacity.

Project partners include 2 universities with established links to food producers ensuring that this project can act as a demonstrator showcasing CO2 reduction opportunities to the other UK food manufacturers.

EdgeMethods and Victrex are developing reusable machine learning models improve energy efficiency within an existing manufacturing plant, to both save on rising energy costs and help achieve sustainability objectives.

Following a successful Proof of Science project, EdgeMethods will implement its ‘Energy of Things’ SaaS solution within the Victrex polymer manufacturing site in North-West England. The project will retrofit energy meters to existing plants, and collect data from existing operational and business systems. Data will be processed on the cloud platform and presented to data scientists for analysis.

The project will align with Victrex’s digital transformation programme, sustainability programmes, following ISO50001 principles. The societal focus on climate change and energy efficiency in the future will attract investment and jobs, and this project will be well positioned to take advantage of emerging opportunities. Across the UK manufacturing sector, improved energy data analytics is thought to result in energy cost and carbon savings of 20-50%, and result in high skilled data science jobs at every manufacturing plant.

Environment Centred Optimisation of SME Productivity using Realtime INTelligence (ECO-SPRINT) - focuses on the aligned sustainability & productivity needs of manufacturing SMEs. Starting with a focus on energy-intensive aerospace special finishing processes it will go on to demonstrate scalability through deployment in other sectors. The project will combine various cutting-edge technologies into which sustainability intelligence capability will be integrated – including vision intelligence; IoT sensors; a Smart Manufacturing Execution System (MES); and a "customer portal" giving foresight of demand.

ECO-SPRINT will take a triple bottom line approach and enable SMEs to:

• capture appropriate insight into manual operations to enable optimisation, risk reduction and digitalised knowledge transfer
• enable real-time optimisation of operations (for productivity and sustainability) based on customer demand, resulting in major savings in energy costs and carbon footprint
• gather data on energy, carbon and material footprint that can be communicated and aggregated across supply chains (e.g., through Valuechain's supplier and customer portals)

PragmatIC will lead a consortium of industry leaders to development new digital technologies and methodologies that focus on decreasing carbon emissions, improving resource efficiency and improving productivity of semiconductor manufacturing.

INSPIRE will use sensors across the manufacturing process to create new AI data models to optimise the consumption, quality, recovery and recycling of energy and critical resources.

INSPIRE is an opportunity to develop best practices for sustainable, smart manufacturing – not just within the semiconductor industry but across other similar industries across the world.

New jobs will be created during the project across data analysis, software engineering, equipment engineering, maintenance, project-management, LCA/Circular Economy specialists. Successful exploitation of project outputs is expected to support additional job growth across the whole consortium and supply-chain.

One of the biggest barriers to scaling the circular economy is maintaining visibility and control over manufactured materials when they enter the waste system. The circular economy dictates that this material or product should be retained at its highest utility, ideally never becoming a waste in the first place.

This project aims to turn the waste system into an 'efficient materials supply chain' that will more readily enable the identification and recovery of industrial by-products/waste and post-consumer material.

The project builds on Topolytics' existing position as a leading player in the global 'wastetech' sector - using mapping and machine learning to make the world's waste visible, verifiable and valuable. Topolytics WasteMap(r) platform ingests, normalises and analyses waste data at scale, from a range of sources, in order to generate insights for waste producers, the waste industry, investors and regulators. The innovation in this project will enable Topolytics to bring together data from manufacturers of consumer products, industrial products and packaging further developing its data science approach to tracking material through the waste system in order to generate more and better insights for manufacturers that enables increased sustainability of UK manufacturing - specifically tackling waste reduction, re-use of resources and associated reductions in carbon emissions.

AI has a crucial role to play in building resilience into the UK Steel industry. In a project led by Deep.Meta the UK based Start Up, who’s founder is an Imperial College PhD graduate, focuses on reducing energy usage in steel production and subsequently carbon emissions across the supply chain through efficiency gains using AI. Efficiency gains at steel plants will be passed on to end-users using steel in construction, hence reducing the embodied carbon from waste in this sector by some 6% over the course of the project while retaining competitive steel prices. This will help to take UK Steel producers to the next level of technological advancement and become increasingly competitive internationally with projected revenue increases of £80 million and the creation 100 new jobs in the UK Steel-Tech sector in the next four years.

Approximately 25% of global plastic production is manufactured in China. Reshoring manufacturing to the UK will drive two major impact reductions: carbon emissions and virgin plastic consumption.

Batch.works is a UK manufacturer who combines 3D-printing and recycled materials to produce products for UK brands, including lighting, stationery, fashion and homeware. In this project we will integrate AI to reduce the fail-rate of 3D-printing and automate our factor processes to:

• Increase use of recycled materials
• Reduce our costly printing fail rate to improve resource efficiency
• Improve life-cycle circularity for new products
• Reduce embodied carbon in our products
• Improve profitability as we scale
• Building UK manufacturing capability that is inherently adaptable, makes us more resilient and less reliant on global supply chains, which have been vulnerable under COVID.

This project will develop an application of digital technologies within wire coiling manufacturing and bed making.

Harrison Spinks is the UKs leading innovator in bed and fine-wire spring manufacturing and is carbon-neutral+ accredited. Its recent innovations in ecologically advanced products and processes have reduced CO2 significantly. It now looks to drive additional innovation in data capture and harvesting from its machining processes to identify waste and improve energy and materials management. This will allow large scale take up of carbon-neutral beds and wider cushioning products, replacing foam with spring technology in several sectors.

Consortium partners are Bespoke Automation Controls Solutions, with expertise in machine programming languages and the Manufacturing Technology Centre, who have deep experience in digitised factory projects.

The consortium will develop a demonstrator, based on Harrison Spinks production processes. Additionally, a new tool will be developed for other manufacturers to support their take up of digitised solutions for CO2 reductions. The project will take two years and will draw on team experience and expertise in machine learning, networking and Industrial Internet of Things technologies.

Project COMPASS is a collaboration between Domin and Ai Build to help Domin scale their additive manufacturing (AM) based manufacturing processes and address demand in the global hydraulics industry.

The application of AI, data science for process analysis and IIoT/connectivity is expected to scale Domin's production capacity, and yield strong improvements in resource efficiency (21.19 tonnes material, 34.65 tonnes CO2e) and energy efficiency (937.71 MWh, 218.39 tonnes CO2e) over three years from project completion. Domin will also accelerate the development of IIoT-enabled AM quality control tools for high-speed fatigue testing and AM metal depowdering, which will help global companies adopt and scale AM within their ecosystem.

The project outcomes are expected to contribute significant Gross Value Add (GVA) to the hydraulics and AM sectors. Further, the consortium will create 7-11 digital technology jobs in the UK during the project, with the scope to create 100s of further new jobs within the following 5 years.

Low Energy Autonomous Digital Factory is a novel project that will establish and validate a new method of digitally manufacturing parts in scale, in a completely autonomous manner. Currently Additive Manufacturing provides huge benefits, but virtually no product is mass manufactured with 3D printers.

LEAD is the culmination of years of development work by Photocentric, a UK research-based SME, into a new field of 3D Printing using LCD screens to harden liquids. Creating parts digitally has numerous energy, productivity, and waste reduction benefits; and parts can be supplied immediately in the quantity required here in the UK. This offers the potential of being a disruptive game-changing alternative to injection moulding where tools are often made in China.

This project intends to be the trigger for starting the next digital industrial revolution of manufacturing, here in the UK, creating new digital manufacturing skills and jobs.

Food production and supply is the backbone of our society -- it is also currently unsustainable. Current challenges of climate and environmental change are a threat and the role of digital technology in facilitating solutions will be demonstrated in this Project.

This project brings together over 220 members of staff from the factory, transport and office functions in the consortium lead, Raynor Foods. It will provide them with meaningful information that will change practice and behaviour so that measurable sustainable outcomes will be reported utilising gamification research to build 'Carbon Hero' games.

Our project will deploy and fuse an array of digital technologies into Raynor Foods sandwich factory in Chelmsford, measuring the CO2e footprint in real-time and making it visible to all operational staff so that they act to reduce it.

The integrated use of IDTs will ensure that all factory processes and assets are measurable, traceable, trackable and controllable. This will provide instantaneous measures of resources and CO2e emissions that will be integrated with staff welfare.

Bringing together process and people data is transformative and enables remedial actions to be owned by staff and made in real time. The process and people data will be input into a Semi-Automatous Management System (SAMS) using AI/ML. SAMS will assist staff to simultaneously reduce factory energy consumption, process waste and monitor and enhance staff welfare and engagement. The digitally-enabled solutions capturing data for energy reduction and production losses will help other industrial sectors that have similar challenges in needing to drive down CO2 impact.