A factory that can shrink or expand its output as easily as a rubber band stretches and snaps back could transform how we make cars, planes, and food. Today, manufacturers in highly regulated industries like aerospace, automotive, and food struggle to scale production up or down quickly and cheaply because their equipment and processes are fixed. This project proposes "elastic manufacturing systems" — a new concept borrowed from materials science and cloud computing — in which production capacity is delivered as a flexible service, not a fixed asset. The system would use collective decision-making and smart, context-aware machines to adjust output in real time, while still meeting strict regulatory standards. If successful, manufacturers could respond to sudden demand spikes or supply chain disruptions without costly retooling or idle capacity. For consumers, this could mean fewer shortages and lower costs for everyday goods. The research will be tested in laboratory rigs and real industrial pilots, with an advisory board steering priorities over four years.
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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.
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