Reliability

By S. Keller-McNulty, Alyson Wilson, C. Anderson-Cook. 2007

228 citations recorded by the source corpus.

This special volume of Statistical Sciences presents some innovative, if not provocative, ideas in the area of reliability, or perhaps more appropriately named, integrated system assessment. In this age of exponential growth in science, engineering and technology, the capability to evaluate the performance, reliability and safety of complex systems presents new challenges. Today's methodology must respond to the ever-increasing demands for such evaluations to provide key information for decision and policy makers at all levels of government and industry--problems ranging from international security to space exploration. We, the co-editors of this volume and the authors, believe that scientific progress in reliability assessment requires the development of processes, methods and tools that combine diverse information types (e.g., experiments, computer simulations, expert knowledge) from diverse sources (e.g., scientists, engineers, business developers, technology integrators, decision makers) to assess quantitative performance metrics that can aid decision making under uncertainty. These are highly interdisciplinary problems. The principal role of statistical sciences is to bring statistical rigor, thinking and methodology to these problems.

Subfields: Control and Systems Engineering, Safety, Risk, Reliability and Quality, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/31f12f737804c73796b980c1edfd1b4ed24c5105

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Kok-Kwang Phoon
2. Dianqing Li
3. Manuel Chiachio
4. Juan Chiachio
5. G. Rus
6. Xiao-Song Tang

In Safety, Risk, Reliability and Quality

1. Dianqing Li
2. Kok-Kwang Phoon
3. Xiao-Song Tang
4. Z. Cao
5. Dong Zheng
6. Manuel Chiachio
7. Juan Chiachio
8. G. Rus

In Statistics and Probability

1. Dianqing Li
2. Xiao-Song Tang
3. Z. Cao
4. Kok-Kwang Phoon
5. Dong Zheng
6. Manuel Chiachio
7. Juan Chiachio
8. G. Rus

Citations in the corpus

• Reliability in composites – a selective review and survey of current development (2012, methodology): “Special attention require SUBSET Simulation [86] and 2SMART algorithms [87], which confer large efficiency as compared to crude MCM, overall for small failure probabilities and high dimension problems [88].”
• Response surface methods for slope reliability analysis: Review and comparison (2016, methodology): “The geometry of the and it is calculated as (e.g., Schuëller and Pradlwarter, 2007; Au et al., 2007):”
• Uncertainty analysis of complex structural systems (2009, unknown): “Other variants of subset simulation are presented in [44, 45] in which splitting is proposed for increasing the efficiency of the algorithm.”