Title :
Uncertainty Analysis of Weibull Estimators for Interval-Censored Data
Author :
Vittal, Sameer ; Phillips, Randolph
Abstract :
The two-parameter Weibull is one of the most popular statistical distributions used to describe the reliability and time-to-failure characteristics of mechanical systems. This paper deals with a Monte Carlo approach to quantify two major sources of uncertainty in Weibull analysis that are commonly found in industrial applications - parameter error introduced due to extended inspection intervals, and error due to different estimation algorithms for interval-censored data. The objective of this paper is to describe some of the numerical methods and processes used to estimate interval-censored Weibull parameters and estimate their bias for a typical industrial application.
Keywords :
Monte Carlo methods; Weibull distribution; failure analysis; reliability; statistical analysis; Monte Carlo approach; Weibull estimators; estimation algorithms; extended inspection intervals; industrial applications; interval-censored data; mechanical systems; parameter error; reliability; statistical distributions; time-to-failure characteristics; uncertainty analysis; Algorithm design and analysis; Inspection; Maximum likelihood detection; Maximum likelihood estimation; Mechanical systems; Monte Carlo methods; Parameter estimation; Statistical distributions; Uncertainty; Weibull distribution;
Conference_Titel :
Reliability and Maintainability Symposium, 2007. RAMS '07. Annual
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-9766-5
Electronic_ISBN :
0149-144X
DOI :
10.1109/RAMS.2007.328067