Dependent Competing Risks in Reliability and Maintainability Assessment

Completed

Other Cross-Cutting Technologies or Research
Other Power and Storage Technologies

Basic and strategic applied research

SOCIAL SCIENCES (Business and Management Studies)

Not Cross-cutting
Other

Professor T Bedford
Management Science
University of Strathclyde

Standard

EPSRC

01 October 2005

31 January 2009

40 months

£159,005

Mathematical sciences

Scotland

Mathematical Sciences

Professor T Bedford, Management Science, University of Strathclyde

Project Contact, Scottish Power Ltd

It costs a lot of money to maintain big pieces of equipment. For example, when a power station fails unexpectedly then 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 on the electricity spot market. By collecting data about the time taken until equipment fails we hope to determine the chance the equipment will work past a certain length of time. Unfortunately very 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 might fail and decided to maintain it "just in case". It is particularly the "just in case" preventive maintenance that 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 beforeit fails. Otherpreventive 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 are developing models that take account of different possible ways of performing preventive maintenance, so that we can take account of the preventive maintenance when analysing the failure data. We shall also look at the way different failure modes can interact so that we can 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 thesituation 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 going to be performed with help from Scottish Power who will provide both staff time and data

01/01/07