To be truly responsive, a manufacturing system should be able to rapidly adapt to what the production need is at a specific time, depending on demand rather than on capacity. Conventional automation cells tend be fixed and specifically designed to manufacture a single or limited number of products in large volumes. However, where product volumes or types are highly variable this approach is inefficient and costly. More resilient approaches that can rapidly adapt to variations in product quantity and type are of great interest and a significant quantity of work has been carried out to realise this concept. However, whilst physical reconfiguration, ie. the positioning of robots and process systems, is relatively easy to achieve, the major barrier is the need for time consuming and costly reprogramming to support each change. The research we propose will take a more holistic view of the reconfiguration process and develop new algorithms that can automatically generate programme and configuration data from CAD and process data eliminating the need for significant human input. Furthermore the system will also consider safety and how to automatically configure the safety system so that it is safe and legally compliant but also implement a flexible framework that allows the active intervention of human operators. Within the research we bring together experts in Robotics, AI and Control and Automation from three leading Universities to work together and develop game changing approaches to resilience in manufacturing. We will also engage with a number of end users and suppliers to ensure that the developed science has real world relevance and is aligned with realistic industrial challenges.

Society complexity and grand challenges, such as climate change, food security and aging population, grow faster than our capacity to engineer the next generation of manufacturing infrastructure, capable of delivering the products and services to address these challenges. The proposed programme aims to address this disparity by proposing a revolutionary new concept of 'Elastic Manufacturing Systems' which will allow future manufacturing operations to be delivered as a service based on dynamic resource requirements and provision, thus opening manufacturing to entirely different business and cost models. The Elastic Manufacturing Systems concept draws on analogous notions of the elastic/plastic behaviour of materials to allow methods for determining the extent of reversible scaling of manufacturing systems and ways to develop systems with a high degree of elasticity. The approach builds upon methods recently used in elastic computing resource allocation and draws on the principles of collective decision making, cognitive systems intelligence and networks of context-aware equipment and instrumentation. The result will be manufacturing systems able to deliver high quality products with variable volumes and demand profiles in a cost effective and predictable manner. We focus this work on specific highly regulated UK industrial sectors - aerospace, automotive and food - as these industries traditionally are limited in their ability to scale output quickly and cost effectively because of regulatory constraints. The research will follow a systematic approach outlined in to ensure an integrated programme of fundamental and transformative research supported by impact activities. The work will start with formulating application cases and scenarios to inform the core research developments. The generic models and methods developed will be instantiated, tested and verified using laboratory based testbeds and industrial pilots (S5). It is our intention that - within the framework of the work programme - the research is regularly reviewed, prioritised and and flexibly funded across the 4 years, guided by our Industrial Advisory Board.

The future prosperity of the UK will increasingly depend on building and maintaining a resilient and sustainable manufacturing sector that can respond to changing supply and demand by adapting, repurposing, relocating and reusing available production capabilities. The pandemic which emerged in 2020 has influenced our perspective of future manufacturing operations and, in particular, has brought into focus the capacity challenges of delivering critical products and maintaining production in the face of major disruptions. It also accelerated the emerging trend for more localised, greener and cost-competitive indigenous manufacturing infrastructure with the ability to produce a wider set of complex products faster, better and cheaper. To meet the long-term structural and post-pandemic challenges, we need transformative new methods of building and utilising future factories by embracing complexity, uncertainty and data intensity in a dynamic and rapidly changing world. The "Morphing Factory" Made Smarter Centre aims to deliver a platform for next generation resilient connected manufacturing services. It will allow future manufacturing operations to be delivered by ubiquitous production units that can be easily repurposed, relocated and redeployed in response to changing market demand. This vision will be delivered through 3 closely related strands: (1) An underpinning fundamental research programme to define the principles, methods and models for future morphing factories in terms of architecture, topology, configuration methods, IoT digital awareness, in-process monitoring and AI based autonomous control. (50%). (2) A dynamic challenge-driven applied research programme to address emerging industrial needs and validate and demonstrate the results through a set of application studies including smart machining, production integrated 3D printing and autonomous assembly integrated into a common hyperconnected morphing factory cloud (45%). (3) A programme of networking and engagement activities with other ISCF Made Smarter research and innovation centres, industry and the general public to maximise the impact of the research, encourage accelerated technology uptake and increase the public awareness (5%).