Reducing over-conservative expert failure rate estimates in the presence of limited data: A new probabilistic/fuzzy approach

Unique highly reliable components are typical for aerospace industry. For such components, due to their high reliability and uniqueness, we do not have enough empirical data to make statistically reliable estimates about their failure rate. To overcome this limitation, the empirical data is usually supplemented with expert estimates for the failure rate. The problem is that experts tend to be - especially in aerospace industry - over-cautious, over-conservative; their estimates for the failure rate are usually much higher than the actual observed failure rate. In this paper, we provide a new fuzzy-related statistically justified approach for reducing this over-estimation.