Department of Engineering / Research / Strategic Themes / Uncertainty Risk and Resilience / Projects

Department of Engineering



We live in an era of abundant data, and the availability of large amounts of data has had a major impact on society, commerce, and the sciences. Data plays a particularly important role in the sciences. We need better tools to model this data, so that we can understand and test theories and make scientific predictions. Our proposal focuses on advanced statistical tools for modelling data. This proposal is truly cross-disciplinary in that we do not focus on a single scientific discipline. In fact, we have assembled a team whose expertise spans Bayesian modelling across the physical, biological and social sciences.

The key challenges facing research, development and deployment of autonomous systems require principled solutions in order for scalable systems to become viable. This proposal intertwines probabilistic (Bayesian) inference, model-predictive control, distributed information networks, human-in-the-loop and multi-agent systems to an unprecedented degree. The project focuses on the principled handling of uncertainty for distributed modelling in complex environments which are highly dynamic, communication poor, observation costly and time-sensitive.

The design of supply networks is traditionally driven by operational drivers of cost, quality, and timely/dependable supply. However, sustainability considerations in network design are now becoming increasingly critical and this project seeks to integrate capabilities in the simulation and modelling of operations (Indian Institute of Technology, Ropar and Indian Institute of Management, Lucknow) and industrial supply network design (University of Cambridge Institute for Manufacturing) toward the development of a new capability in the engineering driven design of sustainable supply networks.

This project explores food safety issues and presents a prototype approach to evaluate and manage food safety especially in cross border supply chains involving best practices, international regulatory requirements and procurement strategies adopted by the food manufacturing firms.

This project focuses on issues which impact on the future viability of key infrastructure over its life as it is affected by both unplanned events [e.g, climate shifts] and also changes in usage mode. A specific aspect of this project is to investigate the future proofing of infrastructural information, examining different technologies and methodologies for ensuring information relating to key infrastructure remains current and accessible.

This project explores implications of climate change on global supply network, which includes raw materials, platform, facilities including plant and geographical locations, product, employees, customers and supporting infrastructure. The effects of climate change, and a greater prevalence of associated extreme events, need to be included into supply network design for resilience. By integrating climate forecast scenarios with supply network configuration theories, a conceptual framework will be proposed for systematically identify and manage key sources of climatic risks in global supply network.

This project is examining alternative models for the use of runways at Heathrow airport. Involving not only Heathrow but also NATS and CAA a series of trials have been run in 2011-13 to determining whether different landing and departure approach will reduce congestion of the runways and add resilience in the face of weather variations and air space delays. Currently simulation models of Heathrow airspace and landing patterns are being developed to take this work further.

A manufacturing responsiveness auditing approach is being adapted in conjunction with UK salad vegetable producer G’s Growers to develop a more broadly applicable tool for assessing resilience of an operation and in the case of G’s to assess whether different operational disruptions can be absorbed effectively.

This project, which is funded by the Boeing Company, aims to develop a system which will make predictive interpretations about potential supplier operational disruptions.

This work aims to understand, and make explicit, risk analyses and communication in the roadmapping approach. The investigation is being carried out in the context of its application to foresight, an approach receiving increasing attention due to its crucial position in fostering sustainable innovation and strategy.