A Methodology for Consideration of Uncertainty in Lifetime Design of Experiments

After a short introduction, approaches are presented which allow the use of Design of Experiments DoE in the case of non-normal distributed data (Weibull, etc Therefore that models are called Lifetime-DoE models (L-DoE models). In order to take uncertainty into account, the classic DoE approach is a...

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Bibliographic Details
Main Authors: Kremer, Alexander, Bertsche, Bernd
Format: Conference Proceeding
Language:English
Subjects:
Accelerated Life Tests
Confidence Interval
Data models
Design of Experiments
Distributed databases
Mathematical model
Maximum likelihood estimation
Planning
Regression analysis
Reliability
Uncertainty
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Summary:After a short introduction, approaches are presented which allow the use of Design of Experiments DoE in the case of non-normal distributed data (Weibull, etc Therefore that models are called Lifetime-DoE models (L-DoE models). In order to take uncertainty into account, the classic DoE approach is also extended by integrating the calculation and simulation of confidence intervals (CI). Four methods were used: Fisher, Monte-Carlo, Pseudo and Bootstrap. Finally, the methodology was shown using a fictitious example. It turned out that the Pseudo-CI provides the largest and thus most conservative CI. While the Fisher and Monte-Carlo approaches have the smallest CIs.
ISSN:2577-0993
DOI:10.1109/RAMS.2019.8768906