[ABE-L] Seminário PIPGEs

[Ricardo Sandes Ehlers]

Seminário Conjunto UFSCar/ICMC  - 20/09/2017 (quarta-feira) – 10:00

Local: Sala 43 do DEs-UFSCar

Palestrante: William Q. Meeker, Department of Statistics, Center for
Nondestructive Evaluation, Iowa State University, Ames, Iowa, USA

Título: Inference Based on Data from Superpositions of Identical Renewal
Processes

Resumo: Maintenance data can be used to make inferences about the lifetime
distribution of system components. Typically a fleet contains multiple
systems. Within each system there is a set of nominally identical
replaceable components of particular interest (e.g., two automobile
headlights, eight DIMM modules in a computing server, sixteen cylinders in
a locomotive engine). For each component replacement event, there is
system-level information that a component was replaced, but not information
on which particular component was replaced. Thus the observed data is a
collection of superpositions of identical renewal processes (SRP), one for
each system in the fleet. This paper proposes a procedure for estimating
the component lifetime distribution using the aggregated event data from a
fleet of systems. We show how to compute the likelihood function for the
collection of SRPs and provide suggestions for efficient computations. We
compare performance of this incomplete-data ML estimator with the
complete-data ML estimator and study the performance of confidence interval
methods for estimating quantiles of the lifetime distribution of the
component.
This joint work with Ye Tian (Facebook), Wei Zhang (Genetech), and Luis
Escobar (Louisiana State University).
Key words: Maintenance Data; Maximum likelihood; Recurrence data;
Reliability; Weibull.
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