NDLI: Warranty prediction for products with random stresses and usages

Content Provider	IEEE Xplore Digital Library
Author	Huairui Guo Monteforte, A. Mettas, A. Ogden, D.
Copyright Year	2009
Description	Author affiliation: ReliaSoft Corporation, USA (Huairui Guo; Monteforte, A.; Mettas, A.; Ogden, D.)
Abstract	Making accurate warranty predictions is challenging. It becomes even more challenging when products are operated under random stresses and random usages. Traditional method only uses the average values of these random variables for warranty prediction. The randomness of the variables is ignored, which may result in inaccurate results. This paper presents methods to solve this issue. Solutions for two different situations are discussed. In the first situation, only random stresses are the major concern. In the second situation, both random stresses and random customer usages are considered. Two analytical solutions, the exact and the approximated solution, are provided for each case. The comparison shows that, although they are simple to use, approximated solutions can be very different from the exact results. In this paper, not only the mean value of the warranty prediction, but also the variances and intervals of the prediction are calculated. This is much better because interval estimate provides more information than a simple point estimate. The proposed methods can be applied to many industries such as electronic, automobile and home appliance companies.
Starting Page	72
Ending Page	77
File Size	317282
Page Count	6
File Format	PDF
ISBN	9781424425082
ISSN	0149144X
DOI	10.1109/RAMS.2009.4914653
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-01-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Warranties Stress Life estimation Random variables Predictive models Electronics industry Industrial electronics Automobiles Home appliances Reliability engineering Monte Carlo simulation warranty prediction random stresses random usages stress-strength model
Content Type	Text
Resource Type	Article

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