Department of Statistical Science
Duke University
presents:
Fabrizio Ruggeri
fabrizio@iami.mi.cnr.it
CNR-IAMI, Milano, Italy
"Bayesian Analysis of the Reliability of Repairable Systems"
Abstract: We will review current research on the Bayesian analysis of the reliability of repairable systems, i.e. systems that can be repaired after a failure (possibly of a small component of it), keeping the same reliability level as before the failure. Such a condition is often called `bad-as-old', even if some authors call it `same-as-old'. Repair time is considered negligible, at least with respect to the operating time of the system.
Data from repairable systems can be available in different forms. We could have a unique system, recording its failures up to a given time T (`time-truncated' data) or until a given number of failures occur (`failure-truncated' data). Besides, we could consider k identical systems for which just (random) operating time and number of failures in it are available. In all these cases, failures of repairable systems are often described by means of a non homogeneous Poisson process, namely the Power Law Process.
Results from an ongoing research on failures of gas pipes in a major Italian city will be presented as well.
November 14, 1997
3:30 pm - 4:30 pm
116 Old Chem Building Any questions concerning the seminar may be addressed to Cheryl McGhee @ [919] 684-8029 or e-mail cheryl@stat.duke.edu. Please contact the author(s) directly for reprints etc.