Activity Number:
|
38
- Reliability Insights
|
Type:
|
Contributed
|
Date/Time:
|
Sunday, July 30, 2017 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Quality and Productivity Section
|
Abstract #323431
|
|
Title:
|
Bayesian Inference of Accelerated Life Tests for Lognormal Life Distribution and Inverse Power Relationship
|
Author(s):
|
Ananda Jayawardhana*
|
Companies:
|
Pittsburg State University
|
Keywords:
|
Bayesian Methods ;
Accelerated testing ;
Lognormal Distribution
|
Abstract:
|
A Bayesian method for obtaining predictive distribution for the lognormal life distribution under normal operating stress level is proposed for using failure data from accelerated levels of stress. Constant accelerated stress levels is considered for the study. Model parameters will be estimated by means of posterior distributions and posterior predictive distribution of future failure times. Gibbs Sampler Markov Chain Monte-Carlo (MCMC) approach will be used for the parameter estimation. An example is used to demonstrate the method and a simulation study to show the validity of the method is reported. Simulation study was conducted using R, R2WinBUGS, and WinBUGS software.
|
Authors who are presenting talks have a * after their name.