Assessing Risk of a Serious Failure Mode Based on Limited Field Data


Several consumer product are designed and made so that the chance of failure during the technological life of the product is tiny. Most product units in the sector retire before they fail. Even though the number of failures of such product is small, there's still a want to model and predict field failures for functions of risk assessment in applications that involve safety. Challenges in the modeling and prediction of failures arise as a result of the retirement times are typically unknown, few failures are reported, and there are delays in field failure reporting. Motivated by an application to assess the risk of failure for a specific product, we develop a statistical prediction procedure that considers the impact of product retirements and reporting delays. Based on the developed methodology, we have a tendency to provide the purpose predictions for the cumulative variety of reported failures over a future time period, and corresponding prediction intervals to quantify uncertainty. We have a tendency to additionally conduct sensitivity analysis to assess the results of different assumptions on failure-time and retirement distributions.

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