Reliability

This presentation documents the work of IDA 2024 Summer Associate Emma Mitchell. The work presented details an R Shiny application developed to provide a user-friendly software tool for researchers to use in planning for and analyzing system reliability. Specifically, the presentation details how one can plan for a reliability test using Bayesian Reliability Assurance test methods. Such tests utilize supplementary data and information, including reliability models, prior test results, expert judgment, and knowledge of environmental conditions, to plan for reliability testing, which in turn can often help in reducing the required amount of testing....

To improve test planning for evaluating system reliability, we propose the use of Bayesian methods to incorporate supplementary data and reduce testing duration. Furthermore, we recommend Bayesian methods be employed in the analysis phase to better quantify uncertainty. We find that when using Bayesian Methods for test planning we can scope smaller tests and using Bayesian methods in analysis results in a more precise estimate of reliability – improving uncertainty quantification....

A challenging aspect ofa system reliability assessment is integratingmultiple sources of information, such as component, subsystem, and full-system data,along with previous test data or subject matter expert (SME) opinion. A powerfulfeature of Bayesian analyses is the ability to combine these multiple sources of dataand variability in an informed way to perform statistical inference. This feature isparticularly valuable in assessing system reliability where testing is limited and only asmall number of failures (or none at all) are observed....

Reliability experiments are important for determining which factors drive product reliability. The data collected in these experiments can be challenging to analyze. Often, the reliability or lifetime data collected follow distinctly nonnormal distributions and include censored observations. Additional challenges in the analysis arise when the experiment is executed with restrictions on randomization. The focus of this paper is on the proper analysis of reliability data collected from a nonrandomized reliability experiments....

This tutorial demonstrates how to plot reliability functions parametrically in R using the output from any reliability modeling software. It provides code and sample plots of reliability and failure rate functions with confidence intervals for three different skewed probability distributions the exponential, the two-parameter Weibull, and the lognormal. These three distributions are the most common parametric models for reliability or survival analysis. This paper also provides mathematical background for the models and recommendations for when to use them....

Reliability tests determine which factors drive system reliability. Often, the reliability or failure time data collected in these tests tend to follow distinctly non- normal distributions and include censored observations. The experimental design should accommodate the skewed nature of the response and allow for censored observations, which occur when systems under test do not fail within the allotted test time. To account for these design and analysis considerations, Monte Carlo simulations are frequently used to evaluate experimental design properties....

Despite the importance of acquiring reliable systems to support thewarfighter, many military programs fail to meet reliability requirements, which affectsthe overall suitability and cost of the system. To determine ways to improve reliabilityoutcomes in the future, research staff from the Institute for Defense analysesOperational Evaluation Division compiled case studies identifying reliability lessonslearned and best practices for several DOT&E oversight programs. The case studiesprovide program specific information on strategies that worked well or did not workwell to produce reliable systems....

One of the most powerful features of Bayesian analyses is the ability to combine multiple sources of information in a principled way to perform inference. This feature can be particularly valuable in assessing the reliability of systems where testing is limited. At their most basic, Bayesian methods for reliability develop informative prior distributions using expert judgment or similar systems. Appropriate models allow the incorporation of many other sources of information, including historical data, information from similar systems, and computer models....

This reliability course provides information to assist DOT&E action officers in their review and assessment of system reliability. Course briefings cover reliability planning and analysis activities that span the acquisition life cycle. Each briefing discusses review criteria relevant to DOT&E action officers based on DoD policies and lessons learned from previous oversight efforts. Suggested Citation Avery, Matthew, Jonathan Bell, Rebecca Medlin, and Freeman Laura. DOT&E Reliability Course. IDA Document NS D-5836....

This paper shows how Bayesian methods are ideal for the assessment of complex system reliability assessments. Several examples illustrate the methodology. Suggested Citation Freeman, Laura J, and Kassandra Fronczyk. “Improving Reliability Estimates with Bayesian Statistics.” ITEA Journal of Test and Evaluation 37, no. 4 (June 2015). Paper:

Reliability is an essential element in assessing the operational suitability of Department of Defense weapon systems. Reliability takes a prominent role in both the design and analysis of operational tests. In the current era of reduced budgets and increased reliability requirements, it is challenging to verify reliability requirements in a single test. Furthermore, all available data should be considered in order to ensure evaluations provide the most appropriate analysis of the system’s reliability....

Recently, the principles of Design of Experiments (DOE) have been implemented as amethod of increasing the statistical rigor of operational tests. The focus has been on ensuringcoverage of the operational envelope in terms of system effectiveness. DOE is applicable inreliability analysis as well. A reliability standard, ANSI-0009, advocates the use Design forReliability (DfR) early in the product development cycle in order to design-in reliability. Robustparameter design (RPD) first used by Taguchi and then by the response surface communityprovides insights on how DOE can be used to make a products and processes invariant tochanges in factors....