Our Ambition
Intelligent Digital Tool
Represent the highly complex supply chains by employing innovative tools.
Reimagine Supply Chains
Demonstrate opportunities for reorientation and future novel approaches which push the supply chains well beyond incremental change.
Capacity Building
Deliver capacity building opportunities for early career researchers and professional staffs strengthen and broaden their skills and career opportunities.
Enable RDI Collaborations
Deliver world-leading, innovation-driven research and development collaborations.
Ecosystem building
Grow and strengthen relationships in the UK innovation ecosystem.
Knowledge based society
Deliver high quality research publications that pave future funding opportunities; and embed research and innovation into society.
Systems Thinking
Background & Context
Supply chains are composed of interconnected processes and entities co-evolving in a changing world
Understand the 'bigger picture' is crucial to improve supply chains' resilience and flexibility
Our Approach
Development of generalisable systems-based conceptual models informed by the case studies.
Focus on 'below the surface' dynamics and conditions that shape supply chains' resilience
Collaboration Opportunities
Integration across Case Studies, policy framework development and industry/government/academia collaborations
Research Questions
What internal and external dynamics and conditions contribute to the vulnerability and resilience of supply chains?
What can be done about these elements?
Digital Twin
Background & Context
Predictive methods already exist for manufacturing planning within an enterprise
Simulation technologies are less well established which span the broader supply chain (SC)
Risk and uncertainty remain threats to SC resilience
Our Approach
Discrete Event Modelling (DEM) for resilient SCs
Enhance DEM models to include provision for risk & uncertainty (Stochastic, Agent Based modelling)
Create DEM centred Digital Twin using live data from production environments / SCs as
Research Questions
How can simulation enhance traditional planning & forecasting methods for improved SC resilience?
Can stochastic or agent-based models facilitate approaches to take account of SC risks & uncertainties?
Can a DEM drive / support a SC digital twin?
Collaboration Opportunities
The fundamental modelling approach used here will be agnostic relative to food, fashion and critical minerals.
Data to drive modelling scenarios will be harvested from all three sectors / across project partners.
Networking Activities & Flexible Fund
RiSC+ Network Plus Work Package
Driving a step change in knowledge, connectivity and co-ordination of research organizations and stakeholders in modelling supply chains for resiliency.
Secondment &
IInternship Scheme
IInternship Scheme
RiSC+ Stakeholder
Fund
RiSC+ Modelling
Studies
Strengthen and
broaden ECR skills and career opportunities
Knowledge Transfer Partnerships
(University & Industry)
Industry investment in digital tech
Strengthened relationships & ecosystem around sectors
Research gaps &
follow-on funding priorities identiifed
High quality research publications
Resilient, response and reorientation of supply chains
Highlights
Our Expertise
A community of influential change agents, who are passionate about collaborating and sharing their expert knowledge and industry connections to enable a transformation in how we think about and model current and future SC.
Artificial Intelligence
Machine learning models will be employed, within the context of a digital twin environment, with algorithmic ability to determine optimum solutions, and the power to combine, analyse and learn from vast and disparate data sets.
Multidisciplinary Team
RiSC+ exploits advanced technologies in cyber security, wireless technologies, energy, power and intelligent control, artificial intelligence and scalable computing (Secure Connected Intelligence) alongside expertise in complexity science, supply chain management, food supply chains and architecture; and advisors from industry and government.
Engineering Assets:
Queen’s computing capabilities, AI experts and inhouse industry facing senior engineering team, working in tandem with the academic team to apply cutting edge R&I to build and launch AI-powered digital twins of supply chains
Data Security
Involvement of award-winning UK Innovation and Knowledge Centre for Cyber Security (CIST) at QUB to provide confidence that data is kept secure; and secure design of the digital models, using a hierarchy of autonomous security agents that will ensure confidentiality, integrity and availability of each system component, including ML models.
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