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TITLE: Warranty Prediction Based on Auxiliary Use-rate Information
SPEAKER: Professor William Q. Meeker
ABSTRACT:
Usually the warranty data response used to make predictions
of future failures is the number of weeks (or another unit of real
time) in
service. Use-rate information usually is not available (automobile
warranty
data are an exception, where both weeks in service and number of miles
driven
are available for units returned for warranty repair). With new
technology,
however, sensors and smart chips are being installed in many modern
products
ranging from computers and printers to automobiles and aircraft
engines. Thus
the coming generations of field data for many products will provide
information
on how the product has been used and the environment in which it was
used. This
paper was motivated by the need to predict warranty returns for a
product with
multiple failure modes. For this product, cycles-to-failure/use-rate
information was available for those units that were connected to the
network.
We show how to use a cycles-to-failure model to compute predictions and
prediction intervals for the number of warranty returns. We also
present
prediction methods for units not connected to the network. In order to
provide
insight into the reasons that use-rate models provide better
predictions, we
also present a comparison of asymptotic variances comparing the
cycles-to-failure and time-to-failure models.
Bio: William Q. Meeker is a Professor of Statistics and
Distinguished Professor of Liberal Arts and Sciences at Iowa State University.
He is a Fellow of the
American Statistical Association (ASA) and the American Society for
Quality
(ASQ) and a past Editor of Technometrics. He is co-author of
the books Statistical
Methods for Reliability Data with Luis Escobar (1998), and Statistical
Intervals: A Guide for Practitioners with Gerald Hahn (1991), six
book
chapters, and of numerous publications in the engineering and
statistical
literature. He has won the ASQ Youden
prize four times and the ASQ Wilcoxon Prize three times. He was
recognized by
the ASA with their Best Practical Application Award in 2001 and by the
ASQ
Statistics Division’s with their W.G. Hunter Award in 2003. In 2007 he
was
awarded the ASQ Shewhart medal. He has done research and consulted
extensively
on problems in reliability data analysis, warranty analysis,
reliability test
planning, accelerated testing, nondestructive evaluation, and
statistical
computing.
