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Details of Grant 

EPSRC Reference: EP/T024429/1
Title: Elastic Manufacturing systems - a platform for dynamic, resilient and cost-effective manufacturing services
Principal Investigator: Ratchev, Professor SM
Other Investigators:
Velu, Dr C McFarlane, Professor D Popov, Professor A
Logan, Dr B Kalise Balza, Dr DF Tanner, Professor G
Researcher Co-Investigators:
Dr J C Chaplin Dr G Martinez Arellano
Project Partners:
ATS Applied Tech Systems Ltd BAe Systems (UK) Bentley Motors Ltd
ElectroImpact GKN KUKA Robotics UK Limited
Loop Technology Limited Manufacturing Technology Centre Nestle UK Ltd
Real-Time Innovations Siemens Spirit Aerosystems
Department: Faculty of Engineering
Organisation: University of Nottingham
Scheme: Standard Research
Starts: 01 May 2020 Ends: 30 April 2024 Value (£): 2,803,659
EPSRC Research Topic Classifications:
Design Engineering
EPSRC Industrial Sector Classifications:
Food and Drink Transport Systems and Vehicles
Aerospace, Defence and Marine Manufacturing
Related Grants:
Panel History:
Panel DatePanel NameOutcome
30 Jan 2020 Future Manufacturing System - Exploratory Stream Prioritisation Panel Announced
Summary on Grant Application Form
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.
Key Findings
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Potential use in non-academic contexts
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Organisation Website: http://www.nottingham.ac.uk