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Activity Number:
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79
- Contributed Poster Presentations: Lifetime Data Science Section
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Type:
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Contributed
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Date/Time:
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Monday, August 3, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Lifetime Data Science Section
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Abstract #309901
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Title:
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Prediction of Future Failures for Heterogenous Reliability Field Data
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Author(s):
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Colin Lewis-Beck* and Qinglong Tian and William Meeker
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Companies:
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University of Iowa and Iowa State University and Iowa State University
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Keywords:
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Reliability ;
Bathtub hazard;
Censored data;
Bayesian;
Prediction
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Abstract:
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This paper introduces a Bayesian approach for using lifetime data to construct prediction intervals for future failures. We first present the generalized limited failure population (GLFP) model. This five-parameter model for lifetime data accommodates lifetime distributions with multiple failure modes: early failures (sometimes referred to in the literature as “infant mortality”) and failures due to wearout. We fit the GLFP model to a heterogenous population of lifetime data using a hierarchical modeling approach. We then predict the number of future failures for each sub-population using an approximation of the Poisson-binomial distribution. We evaluate our prediction intervals using a small simulation study, and apply our methods to real field data on hard drive reliability.
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Authors who are presenting talks have a * after their name.
