Maximum group sizes for simultaneous testing in high potential risk scenarios

Coolen, F.P.A.

Abstract

When tests are performed in scenarios such as reliability demonstration, two extreme possibilities are to perform all required tests simultaneously or to test all units sequentially. From the perspective of time for testing, the former is typically preferred, but in high potential risk scenarios, for example in the case of possibly disastrous results if a tested unit fails, it is better to have the opportunity to stop testing after a failure occurs. An analogon appears in medical testing, with patients being the ‘units’, if new medication is to be tested to confirm its functionality while possibly severe (side) effects are not yet known. There is a wide range of test scenarios in between these two extremes, with groups of units being tested simultaneously. This article discusses such scenarios in a basic setting, assuming that the total number of required tests has been set, for example based on other criteria or legislation. A new criterion for guidance on suitable test group sizes is presented. Throughout, the aim is for high reliability, with testing stopped in case any unit fails, following which the units will not be approved. Any consecutive actions, such as improvement of the units or dismissing them, are not part of the main considerations in this article. While in practice the development of complex models and decision approaches may appear to be required, a straightforward argument is presented, which leads to results that can be widely applied and easily communicated.

Citation

Coolen, F. (2013). Maximum group sizes for simultaneous testing in high potential risk scenarios. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 227(6), 569-575. https://doi.org/10.1177/1748006x13489483

• Journal Article Type: Article
• Publication Date: 2013
• Deposit Date: Jan 7, 2014
• Journal: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
• Print ISSN: 1748-006X
• Electronic ISSN: 1748-0078
• Publisher: SAGE Publications
• Peer Reviewed: Peer Reviewed
• Volume: 227
• Issue: 6
• Pages: 569-575
• DOI: https://doi.org/10.1177/1748006x13489483
• Keywords: High risk, Nonparametric predictive inference, Reliability demonstration, Unknown risks, Upper probability, Zero-failure testing.
• Public URL: https://durham-repository.worktribe.com/output/1465560