Course Homepage: Blackboard

Usually Offered: Summer I Semester in odd years (over the summer periods)

Purpose: To expose the student to the basic concepts of reliability models and statistical inference for various probability models and methods used in life testing and reliability assessment, including parametric and nonparametric models, graphical methods, and classical and Bayesian inference procedures.

Current Textbook: Reliability Modelling: A Statistical Approach, Linda C. Wolstenholme, Chapman & Hall/CRC, 1999. Supplementary notes are also typically handed out.

 

Topics Covered	Chapters	Time
Introduction and Definitions of Reliability	1	0.5 weeks
Lifetime distributions - Representations and interpretations, continuous and discrete lifetime models, system lifetimes, classes.Parametric Models - Exponential, Weibull, extreme value, gamma, lognormal, etc.	2	1 week
Reliability of coherent systems - series, parallel, k-out-of-n, pivotal decomposition, minimum cuts and paths, reliability bounds, etc.	6	1.2 weeks
Nonparametric Reliability Estimation - Censored data; the Kaplan-Meier - PL estimator.	3	1.3 weeks
Parametric models and inference based on likelihood methods.	4, 9	1.4 weeks
Repairable systems.	5	0.3 weeks
Graphical methods - probability plotting with uncensored and censored data, PL estimator total time on test plots, quantile-quantile plots, Weibull plots.	3, handouts	0.8 weeks
Other topics - Reliability demonstrations tests, Accelerated life tests, Stress-strength models.	9.3,9.8,9.11,10.3,7.5-7.8	0.9 weeks
Bayesian methods - Review of prior and posterior distributions, loss functions, Bayes estimator of reliability, etc.	10.8	0.6 weeks

Contact Faculty: Francisco Vera, Edsel A. Peña
(Last Updated: July 11, 2008)