Analysis of split‐plot reliability experiments with subsampling

Reliability experiments are important for determining which factors drive product reliability. The data collected in these experiments can be challenging to analyze. Often, the reliability or lifetime data collected follow distinctly nonnormal distributions and include censored observations. Additio...

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Veröffentlicht in:Quality and reliability engineering international 2019-04, Vol.35 (3), p.738-749
Hauptverfasser: Medlin, Rebecca M., Freeman, Laura J., Kensler, Jennifer L.K., Vining, G. Geoffrey
Format: Artikel
Sprache:eng
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Zusammenfassung:Reliability experiments are important for determining which factors drive product reliability. The data collected in these experiments can be challenging to analyze. Often, the reliability or lifetime data collected follow distinctly nonnormal distributions and include censored observations. Additional challenges in the analysis arise when the experiment is executed with restrictions on randomization. The focus of this paper is on the proper analysis of reliability data collected from a nonrandomized reliability experiments. Specifically, we focus on the analysis of lifetime data from a split‐plot experimental design. We outline a nonlinear mixed‐model analysis for a split‐plot reliability experiment with subsampling and right‐censored Weibull distributed lifetime data. A simulation study compares the proposed method with a two‐stage method of analysis.
ISSN:0748-8017
1099-1638
DOI:10.1002/qre.2394