Expert judgement & reliability
Expert engineering judgement plays a vital role in assessing and modelling the quality and reliability of systems. This can be particularly true of items with high reliability. This is because they have few data failures so understanding the weaknesses in design is much more reliant on engineering judgement.
The same is also true where the inherent reliability is changing. Historical data is not representative of the current state of the system, such as in cases where items are under development, so reliability grows or decays when items near the end of their useful life.
In our research we seek to provide appropriate decision support concerning optimal management of these assets. This requires a deep understanding of the problem that only expert judgement can provide. A key input into our model from this judgment is a subject probability to represent the uncertainty of the expert. Presenting subjective judgements as formal probability distributions can be difficult.
Eliciting engineering knowledge about reliability during design - lessons learnt from implementation
Hodge, R. J. J., Evans, M., Marshall, J., Quigley, J. L. & Walls, L. A. 2001 In: Quality and Reliability Engineering International. 17, 3, p. 169-179
Building prior distributions to support Bayesian reliability growth modelling using expert judgement
Walls, L. A. & Quigley, J. L. 2001 In: Reliability Engineering and System Safety. 74, 2, p. 117-128
Eliciting subjective probability distributions from groups
Daneshkhah, A., Revie, M., Bedford, T., Walls, L. & Quigley, J. Feb 2011 Wiley Encyclopedia of Operations Research and Management Science. Cochran, J. J., Cox, Jr. , L. A., Keskinocak, P., Cole Smith, . J. C. S. & Kharoufeh, J. P. (eds.). John Wiley & Sons Inc.
Prior distribution elicitation
Quigley, J. L., Bedford, T. J. & Walls, L. A. 15 Mar 2008 Encyclopaedia of Statistics in Quality and Reliability. Ruggeri, F., Kenett, R. & Faltin, F. (eds.). John Wiley & Sons Inc.,