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Statistical analysis of marginal count failure data.

M R Karim·W Yamamoto·K Suzuki
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Abstract

Manufacturers want to assess the quality and reliability of their products. Specifically, they want to know the exact number of failures from the sales transacted during a particular month. Information available today is sometimes incomplete as many companies analyze their failure data simply comparing sales for a total month from a particular department with the total number of claims registered for that given month. This information--called marginal count data--is, thus, incomplete as it does not give the exact number of failures of the specific products that were sold in a particular month. In this paper we discuss nonparametric estimation of the mean numbers of failures for repairable products and the failure probabilities for nonrepairable products. We present a nonhomogeneous Poisson process model for repairable products and a multinomial model and its Poisson approximation for nonrepairable products. A numerical example is given and a simulation is carried out to evaluate the proposed methods of estimating failure probabilities under a number of possible situations.

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AlgorithmsData Interpretation, StatisticalEquipment Failure AnalysisModels, StatisticalPoisson DistributionUnited StatesJournal Article

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M R Karim, W Yamamoto, K Suzuki. 2001. Statistical analysis of marginal count failure data.. https://doi.org/10.1023/a%3A1011300907152

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