锁芯断在锁里怎么办:汽车英语翻译，帮忙！！本人还有大量英文需要翻译，谁有意帮忙的？

1. Introduction
Many consumer durable goods—such as automobiles,
appliances and personal computers—include a manufacturer’s
warranty to insure product quality and reliability.
The resulting warranty claims contain field performance
data, obtained under actual operating conditions, which
manufacturers use to track product lifetimes. Majeske,
Lynch-Caris and Herrin [1] show how automobile manufacturers
apply statistical models to warranty data to make
inference regarding product design changes. Manufacturers
also use warranty data to compare actual field performance
with pseudo-lifetime data generated in laboratory or bench
test settings [2].
Automobile manufacturers provide customers with a
basic two-dimensional warranty that quantifies vehicle
lifetime with two metrics: time and mileage. However,
many manufacturers model field performance in the time
domain due to the uncertainty associated with mileage
accumulation. Wasserman [3] and Robinson and McDonald
[4] define the statistic RetT-claims per thousand vehicles
reported cumulatively by month in service-a non-parametric
model that automobile manufacturers use to track warranty
performance. Wasserman [3] develops a dynamic linear
predictive model for RetT using data from multiple model
years of a given vehicle. Robinson and McDonald [4]
suggest plotting RetT on log–log paper and fitting a line to
the observed data. Singpurwalla and Wilson [5] develop a
bi-variate failure model for automobile warranty data
indexed by time and mileage. They derive the two marginal
failure distributions and present a method for predicting RetT
using a log–log model.
Manufacturers also use parametric models for automobile
warranty data. Kalbfleisch, Lawless and Robinson
[6] develop a Poisson model for predicting automobile
warranty claims in the time domain. Moskowitz and Chun
[7] suggest using a bi-variate Poisson model to predict
claims for a two dimensional warranty by fitting the
cumulative Poisson parameter l with various functions of
time and mileage. Hu and Lawless [8] suggest a technique
for modeling warranty claims as truncated data that assumes
warranty claims follow a Poisson process. Oh and Bai [9]
present a method for augmenting parametric warranty data
models with selected observations from products whose
lifetime exceeded the warranty period.
The warranty modeling techniques cited above fit
warranty data using parametric and non-parametric techniques.
To make inference on product features or design
changes, the authors suggest stratifying data or making
0951-8320/03/$ - see front matter q 2003 Elsevier Science Ltd. All rights reserved.
doi:10.1016/S0951-8320(03)00073-5
Reliability Engineering and System Safety 81 (2003) 71–77
www.elsevier.com/locate/ress
* Corresponding author. Tel.: 734-647-6978.
E-mail address: kdm@umich.edu (K.D. Majeske).