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The Greater Manchester AI Foundry

The Greater Manchester AI Foundry is a multi-partner business support initiative that aims to support SMEs in the exploitation of commercial opportunities arising from artificial intelligence.

About the Project

Lancaster University along with partners Manchester Metropolitan University (lead), University of Manchester and University of Salford have been successful in securing funding from the European Regional Development Fund (ERDF) for the AI Foundry project. Artificial intelligence (AI) is a term that has increased in prominence over the past decade and refers to: the use of digital technology to create systems capable of performing tasks commonly thought to require intelligence1.

Support

Available support for participating businesses is broken down into two phases:

Phase 1 support

This is a three-month programme designed to fast-track digital transformation of Greater Manchester's manufacturing sector using Industry 4.0 technology. The programme is designed for mid- to senior-level managers to learn how to solve business problems using the power of Internet of Things (IoT) and Machine Learning (ML). We use an applied blended-learning approach in delivering the three phases of the programme: ideate, innovate, and incorporate.

Through an exclusive partnership with Amazon Web Services (AWS) we bring their IoT, data analytics, AI, cyber, and ML experts together to deliver proof of concepts to support businesses in achieving the following benefits:

  • Increase profitability
  • Increased productivity
  • Reduction in carbon footprint

Phase 1 support is delivered by IN4.0 Group Ltd, in partnership with Lancaster University.

Phase 2 support

Businesses that are selected to receive support from Phase 2 will need to demonstrate growth trajectory in terms of employment increases and development of new products as a consequence of collaborating with Lancaster University. Phase 2 support is bespoke, one-to-one R&D interventions that are tailored to meet business growth needs by exploiting the use of AI within advanced manufacturing, particularly in additive manufacturing.

The team delivering the project at Lancaster is based within our Engineering Department and has expertise in the integration of AI, intelligent control, robotics and additive manufacturing. We aim to collaborate with businesses in Phase 2 in using smart, digital materials for product functionalisation using additive manufacturing. The team has access to a range of processes and facilities that enable part-fabrication in a range of materials.

Eligibility Criteria

To be eligible to receive support from the AI Foundry, businesses must be defined as a small to medium-sized enterprise (SME) and be located in Greater Manchester. Businesses will need to provide baseline company data including declaring details of any state aid received in the past three years. Eligible businesses may take part in either Phase 1, Phase 2 or both depending on requirements and business growth potential, as outlined above.

Our Team

The core team at Lancaster contributing to the AI Foundry are listed below, which is supplemented by a wider group of academics, researchers, technical and professional services staff. If you would like to learn more about how the AI Foundry could benefit your business, please contact us directly or complete the form below.

Tom Abram

Tom Abram

Senior Project Engineer

+44 (0)1524 593783 D29, D - Floor, Engineering Building
Chris Lambert

Chris Lambert

Programme Manager, PhD student

Lancaster Product Development Unit

+44 (0)7814 076610, +44 (0)1524 594383 D29, D - Floor, Engineering Building
Allan Rennie

Professor Allan Rennie

Professor in Manufacturing Engineering

Centre for Global Eco-innovation , Lancaster Product Development Unit, Structures, Materials and Manufacturing, Work and Health Forum

D28, D - Floor, Engineering Building
Samuel Walsh

Samuel Walsh

Project Engineer (Centre for Digital Innovation)

Expression of Interest

Use this form to express an interest in the Greater Manchester AI Foundry.

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