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Details of Grant 

EPSRC Reference: EP/T005432/1
Title: BEST-Man - Bespoke Evolving Smart Technology for Manufacturing
Principal Investigator: Paoletti, Dr P
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Mech, Materials & Aerospace Engineering
Organisation: University of Liverpool
Scheme: Standard Research - NR1
Starts: 01 October 2019 Ends: 28 February 2022 Value (£): 247,243
EPSRC Research Topic Classifications:
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Panel History:  
Summary on Grant Application Form
We are witnessing incredible advances in manufacturing technologies, with the advent of additive manufacturing and enhanced construction techniques which allow us to produce parts, assemblies and even buildings that would have been

out of reach or extremely expensive just a few years ago. However, the end product of any current manufacturing process is static: once built, the part will preserve its shape and/or physical properties for its lifetime.

However, imagine the endless possibilities that would be available if a structure could dynamically change its shape or physical properties to respond to external stimuli. What if we could create and collectively control thousands of simple

entities? They could act as molecules and connect to each other to form a structure that responds to external forces and other stimuli. Creating such technology would represent a step change in the current manufacturing landscape. The aim of the BEST-Man project is to lay the foundations and create proof-of-principle demonstrators to show that such vision can be achieved.

To reach such an ambitious vision, BEST-Man will blend together elements from a diverse range of disciplines; mathematical modelling and simulations will be used to explore what type of entities, connections between them, actuation

and sensing are required to self-assemble a desired programmable structure; mechanical design and advanced manufacturing will guide the design of individual entities; electronic engineering will serve to implement sensing, control

and actuation; computer science will provide control algorithms that are scalable to thousands of cooperating entities to form smart products.

The final demonstrator will include 1000+ entities capable of self-reconfiguration in presence of external stimuli and/or user input. Examples of demonstrators to be considered include: morphing wing to be tested in a wind tunnel, a dining table which can be split into a smaller table plus a coffee table at the user command, and a self-healing object which uses colours to indicate region of excessive loading/cracks and repairs itself by rearranging entities.
Key Findings
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Potential use in non-academic contexts
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Date Materialised
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Organisation Website: http://www.liv.ac.uk