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 …

Incorporating artificial intelligence (AI) leveraging statistical machine learning (ML) into
complex systems poses numerous challenges to traditional test and evaluation (T&E) …

Engineers use reliability experiments to determine the factors that drive product reliability,
build robust products, and predict reliability under use conditions. This article uses recent …

After more than a decade since the introduction of Statistical Engineering by Roger Hoerl
and Ronald Snee, a group of leading applied statisticians from academia, industry, and …

We propose a Bayesian hierarchical model to assess the reliability of a family of vehicles,
based on the development of the joint light tactical vehicle (JLTV). The proposed model …

The complex, multifunctional nature of defense systems, along with the wide variety of
system types, demands a structured but flexible analytical process for testing systems. This …

When making decisions about whether a product can meet required performance standards,
it is often of interest to make decisions as soon as enough information has been obtained …

In order to master the main malfunction and the law of occurrence of the vehicle which
affects the operational reliability of the Straddle-Type Monorail traffic, this paper, based on …

When developing a system, considering system performance from a user perspective can be
done through operational testing| assessing the ability of representative users to accomplish …

There are many challenges with assessing the reliability of a complex system. One of the
more difficult aspects of system reliability assessment is integrating multiple sources of …