Completed projects
Over the last 10 years, members of the Risk Consortium have carried out research or consultancy for a number of clients. These include, amongst others, Aveco, ESTEC, Goodrich Engine Control Systems, Health and Safety Executive (HSE), Maritime and Coastguard Agency, Ministry of Defence (MOD), NASA, Netherlands Ministry of Water Management, Philips, Railway Safety and Standards Board, Rolls Royce, Scottish Power, SKI, and Valador
Health and Safety Executive project
The Health and Safety Executive sponsored a PhD student to investigate Common Cause Failures (CCFs) in diesel engines in Nuclear Power Plants. CCFs are a class of dependent failures that occur to complex technological systems, such as nuclear power plants, where redundant components serve as multiple layers of defence. For the purposes of quantitative assessment of CCFs, parametric models are used. A common feature of all parametric models is the difficulty in parameter estimation due to limited available observational data. The Unified Partial Method (UPM) for CCF modelling is a systematic methodology that takes into consideration physical and operational system defences.
The researcher explored the application of the Influence Diagram (ID) formalism in order to extend the UPM. The developed model incorporated intermediate stages in the modelling process, namely root causes and coupling factors, to allow for a representation of the CCF mechanisms. Moreover, it captured interactions existing amongst the system’s defences, in their contribution to risk. With an underlying Bayesian approach to risk, the model quantified operational experience, accounted for the epistemic uncertainty, and allowed for a coherent combination of expert opinion with observations. Finally, the ID formalism allows for the propagation of uncertainty within the model structure and provides a tool for decision-making.
United Kingdom Ministry of Defence (MoD)
The Risk Consortium has worked extensively with the MoD over the past few years. This has included short consultancy projects, sponsoring post-doctoral research students, doctoral research students and MSc students, of which a selection are described below.
Reliability management
Dr Revie's doctoral thesis was sponsored by the MoD. Throughout the life of the project, Dr Revie interviewed and discussed the problem with a number of different MoD staff. The problem facing the MoD was attempting to combine, in a logical and structured manner, the different information relating to reliability that becomes available to a decision maker during the life of a procurement project. A Bayes Linear methodology was developed that allowed decision makers.
Sampling techniques
Work sponsored by DOSG has concentrated on the use of structured expert judgement (SEJ) in decision making. EJ is used extensively to aid decision making, but frequently in an ad-hoc, unstructured manner. Our work has been to provide general guidance on the implementation of SEJ processes for the elicitation and use of expert judgements in a way that can be rationally justified. This general guidance has been supplemented by work on specific projects involving the structuring and population of fault-trees, the development of models for quantitative risk analyses and methods for assigning probabilities to low frequency events with little-observed data.
Kwik Fit Insurance Services
The Risk Consortium, in collaboration with the Department of Design, Manufacturing and Engineering Management, evaluated the new business service development process adopted by KwikFit Insurance Services (KFIS).
The project aimed to assess the impact of two different customer experience processes on retention of customers. KFIS were driven by developing techniques to increase their retention rate and wanted to assess different processes they could adopt. The quantitative analysis carried out by the Risk Consortium highlighted the different factors that influenced retention. In addition, a logistic regression model was developed to support KFIS predict the probability of different customers being retained by KFIS based on customer characteristics. This allowed KFIS to develop a pricing strategy to maximise profit.
NASA
Recently, the Risk Consortium completed a project with the National Aeronautics and Space Administration (NASA). This work was different to previous contact with NASA and work with the European Space Agency (ESA), as it looked at risk from a strategic perspective rather than a technical approach. The research examined a number of exploration campaigns that have taken place during the last 700 years and considered them from a risk perspective. The explorations were those led by Christopher Columbus, Sir Walter Raleigh, John Franklin, Sir Ernest Shackleton, the Company of Scotland to Darien and the Apollo project undertaken by NASA.
To provide a wider context for investigating the selected exploration campaigns, ways of finding analogies at mission, programmatic and strategic levels were developed. Ultimately, the purpose of the study was to understand how risk has shaped past explorations, in order to learn lessons for the future. From this, we can begin to identify and develop tools for assessing strategic risk in future explorations.
An important observation from the research was that all the cases – with the exception of Apollo – were failures in terms of meeting their original objectives. However, despite this, several were strategic successes and indeed changed goals as needed in an entrepreneurial way. Graphical analysis models were used to quantitatively assess which risks were realised most often during our case studies and to draw comparisons at a mission, program and strategic level. In addition, using these models and the narrative of each case, specific lessons for future exploration were identified.
There were three key conclusions to the study:
- analyses of historical cases have shown that there exists a set of generic risk classes
- there is no reason to believe that these risk classes will not be applicable to future exploration and colonisation campaigns
- modern risk modelling techniques are capable of addressing mission and program risk but are not as well suited to strategic risk
We observed that strategic risks are prevalent throughout historic exploration and colonisation campaigns. However, systematic approaches do not exist at the moment to analyse such risks. A risk-informed approach to understanding what happened in the past helps us guard against the danger of assuming that those events were inevitable, and highlights those chance events that produced the history that the world experienced. In turn, it allows us to learn more clearly from the past about the way our modern risk modelling techniques might help us to manage the future – and also bring to light those areas where they may not.
Mint Casino
The Risk Consortium carried out a cost-benefit analysis for Mint Casino on a new progressive jackpot addition to Blackjack. Mint Casino proposed two versions of a progressive jackpot game and requested that the Risk Consortium assess the probabilities of a player winning each prize, the expected jackpot of the game when the prize was won and the expected profit for the casino. In addition, the Risk Consortium provided Mint Casino with information on the probability of MintCasino recouping their investment per jackpot won and the optimal amount to place in the jackpot.
Defence Science and Technology Laboratory (DSTL)
The Risk Consortium worked with DTSL to support the development of new safety targets for aircraft. Currently, there is a mismatch between the safety measurement for aircraft, which is in flying hours, and weapon systems which is measured per-event. Through interviews and a review of current literature, a method was proposed to support the assessment of safety targets for new weapon and aircraft systems. In addition, the proposed method was able to support the setting of the operational envelope for aircraft operators in order that HSE targets were met.
Scottish Power
It costs a lot of money to maintain large equipment. For example, when a power station fails unexpectedly, it may cost £20,000 per hour for the first few hours because the electricity that should have been produced has to be bought from the electricity spot market. By collecting data about the time taken until equipment fails it is possible to determine the chance the equipment will work past a certain length of time. Unfortunately, often the equipment doesn't actually fail but is removed from service for some other reason. Maybe something else failed and all the equipment had to be maintained or maybe someone thought that the equipment may fail and decided to inspect it "just in case". The "just in case" preventive maintenance poses a problem for us because we cannot tell how long the equipment would have gone on to work for. Some preventive maintenance may be very good, getting the equipment just before it fails. Other preventive maintenance may be quite poor, occurring at times that have little to do with the actual failure time. To make it even more complicated, equipment can often fail in more than one way (usually called failure modes). This sort of situation is called "competing risks" because there are different mechanisms (for example failure types or preventive maintenance) that are competing to be the first to take the equipment out of service.
In this project, we developed models that take account of different possible ways of performing preventive maintenance. We were able to take account of the preventive maintenance when analysing the failure data. We also looked at the way different failure modes interacted so that we could model what would happen if we tried to delay one failure mode. Often improvements to the system and the method of preventive maintenance do not get made because not enough people are convinced that the change would be for the better. By modelling the situation, we want to build a decision support tool that would enable us to predict the effect of change without doing it in practice. That way we can choose the best course of action at a low cost. In order to ensure that the solutions we come up with are really relevant to practical needs, this project is carried out with help from Scottish Power who provide both staff time and data.
BBi
BBi required a method for establishing and implementing performance benchmarks for the quality of translations, where quality is measured as the number of non-conformances in a translation whose size is measured by the number of words.
The Risk Consortium developed a decision rule based on the number of words in the translation document and the tolerable number of failures. In order to identify the tolerable number of failures, interviews were carried out with translators and BBi management. The Risk Consortium built a model in Microsoft Access to allow BBi to automate the decision rule process. Training was provided to BBi by the Risk Consortium to demonstrate how to use the software and train the appropriate staff.
