JSM 2004 - Toronto

Abstract #301060

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Activity Number: 189
Type: Contributed
Date/Time: Tuesday, August 10, 2004 : 8:30 AM to 10:20 AM
Sponsor: Section on Physical and Engineering Sciences
Abstract - #301060
Title: Reliability Estimation of an Unknown Load Share Rule
Author(s): Paul H. Kvam*+ and Hyoung T. Kim
Companies: Georgia Institute of Technology and Georgia Institute of Technology
Address: 765 Ferst Dr., Atlanta, GA, 30332-0205,
Keywords: maximum likelihood ; software reliability ; order-restricted inference ; system dependence
Abstract:

We consider a multi-component load-sharing system in which the failure rate of a given component depends on the set of working components at any given time. Such systems can arise in software reliability models and in multivariate failure-time models in biostatistics, for example. A load-share rule dictates how stress or load is redistributed to the surviving components after a component fails within the system. We assume the load share rule is unknown and derive methods for statistical inference on load-share parameters based on maximum likelihood. Components with (individual) constant failure rates are observed in two environments: (1) the system load is distributed evenly among the working components, and (2) we assume only the load for each working component increases when other components in the system fail. Tests for these special load-share models are investigated.

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