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The project’s objective is to support the creation of a resilient and sustainable manufacturing sector, that can deliver critical products in the face of major disruptions in a more localised and sustainable manner.

Overview of the Project

Responding to sector needs and opportunity by defining a new type of manufacturing factories that can continuously adapt and be closely connected in a highly responsive manufacturing environment.

 

Made Smarter Innovation Research Centre for Connected Factories proposes a radical new approach to building the manufacturing infrastructure of the future based on autonomous morphing factories, which will challenge traditional manufacturing systems science.

 

This will allow future manufacturing operations to be delivered by ubiquitous production units that can be easily repurposed, relocated and redeployed in response to changing product requirements and volume demand.

We define the autonomous morphing factory as a “self-contained production unit that can continuously adapt its capabilities into different configurations by changing relationships between production resources.” These adaptations are designed to most effectively respond to product and demand variations and internal disruptions. We characterise the factory by 4 key facets:

Agility: Ability to respond to incoming demand and dynamically self-configure and self-organise to adapt to product variations and volume fluctuations.

Autonomy: Ability to interact with the operators and the environment and exhibit self-learning and self-adapting behaviours.

Multifunctionality: Ability to deliver a variety of processes and skills on a single platform.

Resilience: Ability to self-adapt, self-repair, self-calibrate and self-qualify.

 

An autonomous morphing factory is not confined to one location and can be geographically distributed or co-located and individual factories can be closed connected at different levels to form complex morphing manufacturing infrastructure.

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Overview

Delivering the Vision

The vision for the Research Centre for Connected Factories is being delivered through 3 closely related strands: 

 

An underpinning fundamental research programme: To deliver the principles, methods and models for the future autonomous morphing factory in terms of architecture, topology, configuration methods, IoT digital awareness, in-process monitoring and AI-based autonomous control. 

A dynamic challenge driven applied research programme: To address emerging industrial needs and validate and demonstrate the results through a set of application studies.  

A programme of networking and engagement activities with industry, other research centres and the general public: To maximise the impact of the research, encourage accelerated technology uptake and increase public awareness. 

Delivering
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The Applied Research Programme: Our Application Studies

We are working closely with our industrial partners to address emerging industrial needs through a set of application studies to test, validate and demonstrate core principles and methods for connected morphing factories (our Technology Solutions). The Application Studies are exemplars of the morphing factory configuration and behaviour, addressing specific industrial needs. 

Applied

Learn more about our application studies in greater detail. 

Application Studies

Engagement

The Engagement Programme

We are undertaking a broad range of activities involving industry, academia and the general public, with the aim of promoting the Centre, informing our research activities and ensuring we maximise the impact of our research. Our network of industry project partners – those who directly engage with and inform our research activities – includes representatives from key UK industrial sectors including aerospace, automotive, food and beverages, energy and construction. We are always interested in hearing from anyone interested in engaging with the Centre. 

If you are interested in seeing how you could engage with the Centre for Connected Factories please contact Daniel Symes at daniel.symes@nottingham.ac.uk

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