Public Funding for Advanced Manufacturing (Sheffield) Limited

Public description Supply chain resilience is a widely studied topic of significant impact on our society. As organisations outsource production to one another they create economies of scale and reduce prices but also increase the risk of disruption that cascades throughout the entire supply chain if any member of the chain is disrupted. Typically, organisations act alone, rather than as an ecosystem when predicting disruptions and deciding on mitigation strategies. However, disruption data an individual organization can collect and analyse is small, imbalanced, and partial entirely to its own view. When uncertainties increase, this individualistic approach results in short-sighted decisions. Numerous studies proved that _increased data sharing_ and _collective decision-making_ would _increase resilience_, but this has not been plausible as members of the ecosystem fear that information shared can be used opportunistically by other parties. _Federated learning_ is an emerging approach in the Artificial Intelligence field that may help supply chain members collectively optimise resilience while keeping their data private. The approach enables organizational agents to collaboratively develop a shared prediction model. Here, if one organization is able to predict a disruption, its knowledge can be shared sending an early warning signal and giving companies time to respond. As the approach can be automated, costs of manual orchestration are avoided. In this project, we will develop, validate, and compare suitable federated learning models specifically for disruption prediction and collective learning in supply chains with real use cases in the aerospace and manufacturing sectors.

The Stabilisation Support for Aerospace Recovery (ASSURER) project is a support application to balance out some of the increased costs associated with current Aerospace innovation projects as a result of the COVID-19 pandemic. The Aerospace sector has taken a significant hit during the last 18 months, but prior to the pandemic was growing at a significant rate and of major value to the UK economy. Advanced Manufacturing Ltd (AML) were involved in Aerospace productivity project/s which are detailed below in italics for context. _The current business and regional jet aircraft market is expected to expand significantly in the next five years, requiring up to a threefold increase in production rates for higher volume components such as aerofoils for the associated aero-engines. As a result, the supply chain needs to make a step change improvement in its production rates on these types of components._ _As such, the Automotive Excellence in Aerospace (AXIS) project aims to bring together innovative technologies for rate production in automotive applications into an aerospace cell to vastly improve production rates. These technologies combine digital connectivity between supply chain partners, advanced shipping and condition of supply information to drive predictive programming, automated part loading using flexible fixtures, and advanced machining techniques to meet this challenge._ _The principle project output is a functioning demonstration cell for business and regional jet engine aerofoil manufacture with a connected supply chain component. This cell will show the capability to achieve the desired three-fold increase in production rate for this aerofoil component market. The optimised demo cell provides the immediate route for engagement with an OEM in the development of a supply chain contract._ _The innovative aspect of the project is bringing together the four technologies in the work packages into a high rate production aerofoil cell. This includes the digital connectivity, automated loading of aerofoil geometry, adaptive measurement and control, and advanced machining techniques. All have been proven to work in other applications but bringing them together in an automotive style production approach to aerospace is the unique aspect of this project._ The ASSURER project provides financial support to the above project within three specific areas; an increase in raw material costs, an increase in key service subcontracting costs, and the requirement to outsource some production related operations due to lack of staff availability.

The **PREDICTOR** application follows on from previous work conducted on developing a machine learning model to improve machining process design in manufacturing as part of the UK-Canada enhancing industrial productivity programme. The original work was developed specifically for machining operations in manufacturing taking production data and providing recommended solutions and best practice for operational engineers within manufacturing environments. Predictor takes this unique functional model and applies an additional layer of capability by integrating costing information to use learnings from production data to make better predictive estimates for the sourcing of **NEW** component parts. Essentially, the original ML model is helping engineers improve their **bottom-line** value through operational improvements, whilst the additional functionality developed through **Predictor** will allow companies to also expand their **top line** through being able to source parts and orders more cost effectively.

The **RAVINE** project aims to reduce the time impact of the metrology processes carried out by CMM tactile probing for Advanced Manufacturing (Sheffield) Ltd (AML) through the application of rapid visual scanning technologies for complex aerospace components.

The current business and regional jet aircraft market is expected to expand significantly in the next five years, requiring up to a threefold increase in production rates for higher volume components such as aerofoils for the associated aero-engines. As a result, the supply chain needs to make a step change improvement in its production rates on these types of components. As such, AXIS presents a project that aims to bring together innovative technologies for rate production in automotive applications into an aerospace cell to vastly improve production rates. These technologies combine digital connectivity between supply chain partners, advanced shipping and condition of supply information to drive predictive programming, automated part loading using flexible fixtures, and advanced machining techniques to meet this challenge. The principle project output is a functioning demonstration cell for business and regional jet engine aerofoil manufacture with a connected supply chain component. This cell will show the capability to achieve the desired three-fold increase in production rate for this aerofoil component market. The optimised demo cell provides the immediate route for engagement with an OEM in the development of a supply chain contract. The innovative aspect of the project is bringing together the four technologies in the work packages into a high rate production aerofoil cell. This includes the digital connectivity, automated loading of aerofoil geometry, adaptive measurement and control, and advanced machining techniques. All have been proven to work in other applications but bringing them together in an automotive style production approach to aerospace is the unique aspect of this project.

Commercial aviation has been heavily impacted by the Covid-19 pandemic, with significant production disruption combined with decreased demand leading to deferral of aircraft orders. While this will be felt across the industry, SMEs are particularly vulnerable and job losses are expected throughout the sector. To reduce the impact on jobs and market share, AML are proposing a technology development project to help secure both new and existing work supplying critical wear parts for commercial aircraft. AML currently manufactures and supplies advanced bearing products to an aerospace prime and is on the cusp of securing a further major supply agreement with this customer. These products are wear parts on commercial aircraft engines and require replacing on every repair and overhaul visit for every engine in service. The package that AML currently supplies covers both new and older aircraft, particularly those commonly used for freight aircraft, a key sector in the face of the pandemic. As these components are split bearings, the existing process involves an initial wire Electrical Discharge Machining (EDM) split operation. The two halves are then glued together and finish machined, leading to increased cycle times and lead times. If the part could be machined as a complete part and then split at the end, this would drastically increase the overall efficiency of the process. To achieve this, this proposal seeks to develop micro- wire EDM technology for this application. This represents substantial innovation owing to the challenges involved in using such unusually thin wire, on tough, hard materials, to very tight tolerances. Successful implementation will result in reduced lead times, increased efficiency and negation of the risks surrounding glue supply. The immediate impact expected is the protection of jobs and market share at AML, as well as the safeguarding of the supply of advanced bearings for commercial and freight aircraft. In the medium to long term, the development of such novel techniques for manufacture of these parts will put AML and the UK in a strong position to maintain their standing in the aerospace industry in the aftermath of the pandemic. The project extension will provide AML the capability to leverage benefits not only in the commercial aerospace market sector but also within the defence sector too. This involves transferring the innovative wire EDM technology to a new bearing range on a defence product. The impact of this will further secure work for AML in a diversified sector on a complex product line, and allow the company to continue to grow despite the current effects of Covid 19.

The SmartCal project will develop a dynamic calibration system using RFID tagging and advanced software to allow precision manufacturers to drastically reduce non-conformance issues, improve process efficiency and reduce cost in the calibration cycle. This will be achieved through tool degradation, location tracking and smart software.

Awaiting Public Project Summary

Advanced Shaft Manufacturing

The vision is to develop single platform machine for Interrupted HYbrid additive / subtractive Manufacture with integrated inspection technologies -- for the purposes of this bid, defined as IHYM. This will be based on blown powder additive and 5-axis mill-turn machining. We will develop process capability in four application areas where we have identified a business need: § Interrupted processing: the creation of complex internal geometries which can only be achieved through IHYM. § 'Lumps and bumps': Working with slimline forgings or castings and adding external features such as bosses, elbows or ribs to improve material yield and enable rapid customisation of products. § Graded Functionality: control localised material properties through control of lay conditions in conjunction with bulk material - single or multi material. § Titanium: process redesign to enable IHYM with Titanium To deliver these additive capabilities, real-time process information must be obtained and mined for insights. Process monitoring will be linked to real-time or event-based control of the platform through a novel rule-based system which will provide both user feedback and increased machine autonomy. A completely new field is the development of combined process models which will provide insights into the effect of IHYM on part metallurgy. A novel feature-based cost modelling system will also be developed. The project starts at a manufacturing readiness level (MRL) 4 and using the market-leading hybrid platform from DMG Mori, and will deliver hybrid machining techniques to MRL6 for four additive capabilities. Key objectives and innovative developments are: § Novel through-process models and decision systems § Through-process monitoring and control, fed by insights from models § Connected system to fuse knowledge and rules with data analytics § Completely new IHYM ability for Titanium § Manufacturing strategy for intermittent deposition / machining due to heating and cooling effects § Manufacturing capability for graded materials § Development of adjacent processes (powder characterisation and recommendations for standards, novel heat treatments) § Design rules for IHYM Project impacts include: § Acceleration of IHYM uptake because of the automated decision tool and cost model § Reduced material consumption in aerospace and oil and gas components by 60%, linked to the near-net additive manufacture of raw components, thereby replacing or simplifying castings and forgings. § Reduced tooling and associated costs. § 30% reduction in production costs due to the introduction of IHYM technologies, linked to optimised manufacturing conditions and tool path optimisation.

At least 25% of the process time for high value manufactured components arises from machining. CNC machine tools are programmed to produce geometry to a nominal form and surface finish, sources of error in the machining system impact on the cost, quality and delivery. These sources are split into those induced by the condition of the machine tool system and those induced by the behaviour of the work piece. The consortium, comprising machine builders, solution providers, academic institutes and end users, will collaborate to produce a predictive software tool that uniquely integrates both machine and machining models to provide prediction and visualisation of component geometry and surface finish. Machine users will be able to model the effects on part accuracy of machine, work holding, and part flexibilities during a cutting cycle, and design their part programs accordingly, thereby reducing prototyping and production downtime. Machine builders will use the tool to improve the design and efficiency of new product development. The modular solution is a stepping-stone to an all-encompassing model for controlling the accuracy of the machining process.

Metals related manufacturing represents about 10% of all UK production activity and machining Metals related manufacturing represents about 10% of all UK production activity and machining remains the most important manufacturing process. According to the Manufacturing Technologies Association, in 2012 the UK machine tools, cutting tools and tool/work-holding equipment output was estimated to be around £960 million (£835 million exported) and the sector is estimated to employ 6100 people. This project seeks to develop intelligent tooling systems, which will improve the efficiency of machining processes. This project intends not only to support the UK machining sector, but in doing so will generate valuable know how for the UK.