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Details of Grant 

EPSRC Reference: EP/R032777/1
Title: Digital Manufacturing on a Shoestring [Digital Shoestring]
Principal Investigator: McFarlane, Professor D
Other Investigators:
Parlikad, Professor A Ratchev, Professor SM
Researcher Co-Investigators:
Project Partners:
Atos Origin IT Services UK Ltd British Standards Institution BSI BTL Precision
EEF Greater Manchester Chamber of Commerce High Value Manufacturing (HVM) Catapult
Manufacturing Technologies Association Nottinghamshire Manufacturing Network PA Consulting Services Ltd
Precise Component Manufacture Raspberry Pi Foundation Siemens
Warren Services
Department: Engineering
Organisation: University of Cambridge
Scheme: Standard Research
Starts: 01 October 2018 Ends: 31 March 2022 Value (£): 1,667,135
EPSRC Research Topic Classifications:
Design & Testing Technology Manufact. Enterprise Ops& Mgmt
Manufacturing Machine & Plant
EPSRC Industrial Sector Classifications:
Manufacturing
Related Grants:
Panel History:
Panel DatePanel NameOutcome
22 Feb 2018 Manufacturing Prioritisation Panel - Feb 2018 Announced
Summary on Grant Application Form
The digitalisation of manufacturing is a key enabler in the UK Government drive to raise the level of industrial productivity to match and exceed leading competitors. Whilst basic digital technology applications in manufacturing are not new, there are two key trends that predicate the timeliness of the proposed research: (1) manufacturing organisations are increasingly seeing information as a key strategic addition to their product offerings; (2) major innovations in computer science, control and informatics have created new opportunities for major breakthroughs in manufacturing. One of the critical challenges is how to support the digital manufacturing transformation of SMEs and introduce new methods of production that take into account the latest control, communication and AI technologies in a sector characterised by limited capital investment and research potential. Whilst there is significant body of knowledge in this area it is mostly focused on relatively expensive solutions which are often unaffordable to SMEs?

This project will therefore address a common concern that recent developments in digital manufacturing are unlikely to accessible by SMEs owing to the associated capital cost of upgrading industrial computing and communication environments. The project proposes a radically different approach to the digital evolution of a manufacturing operation by focussing predominantly on non industrial solutions to industrial automation and information challenges. It will seek to exploit very low cost commercially available technologies for mobile computing, sensing, AI and tackle the challenges associated with integrating these safely and securely into a small scale manufacturing environment. As well as conventional research activities, the project will more radically involve student hackathons as a means of stimulating low cost software development, will use an in-house technology transfer organisation to access SME organisations, and engage directly with the High Value Manufacturing catapult demonstration network as a means of reaching the maximum number of potential users. Stretch targets for the programme include the introduction of low cost product tracking, exploiting emerging industrial IoT platforms and AI-based flexible control using commercially available AI and voice recognition development environments.

The project will supplement the traditional research and development approaches with some innovative implementation development activities in which (i) undergraduate and graduate students in both engineering and computer science and integrated via a series of hackathons and software and hardware development competitions (ii) a series of workshops will be targeted at local start up and SME IT communities to engage them directly in the development of applications and products (iii) by working directly with technology transfer organisations to ensure that not only the final message but also the starting rationale for the work fully engages the SME manufacturing community.

Key Findings
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Potential use in non-academic contexts
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Summary
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