Weibull Data Analysis with Few or no Failures

Ming-Wei Lu and Cheng Julius Wang
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Ming-Wei Lu: Daimler Chrysler Corporation
Cheng Julius Wang: Daimler Chrysler Corporation

Chapter 8 in Recent Advances in Reliability and Quality in Design, 2008, pp 201-210 from Springer

Abstract: Abstract Laboratory testing is a critical step in the development of vehicle components or systems. It allows the design engineer to evaluate the design early in the reliability development phase. A good lab test will shorten the product development cycles and minimizes cost and part failures at the PG or field testing before the vehicle volume production. Appropriate testing is available to correlate test time in the lab (or lab test bogey) to the real world survival time (or field design life). The testing must be in some accelerated fashion or typically called accelerated testing. The failure mechanism(s) that the accelerated test will bring out is of great importance. No one test can surface all potential failure mechanisms of the part. Certain failure mechanisms dominate throughout the useful lifetime of the part, and some may never occur. To verify a new product design meeting a reliability target requirement, one can perform data analysis on the life testing data by using Weibull life distribution. However, in fitting a Weibull distribution to reliability data, one may have only few or no failures. This paper presents method to estimate the reliability and confidence limits that apply to few or no failures with an assumed Weibull slope value of β.

Keywords: Weibull Distribution; Design Life; Monte Carlo Simulation Technique; Rank Regression; Monte Carlo Trial (search for similar items in EconPapers)
Date: 2008
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DOI: 10.1007/978-1-84800-113-8_8

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