A Sequential Accelerated Life Testing Framework for System Reliability Assessment with Untestable Components

[+] Author and Article Information
Zhen Hu

Assistant Professor, Department of Industrial and Manufacturing Systems Engineering, University of Michigan-Dearborn, 2340 Heinz Prechter Engineering Complex (HPEC), Dearborn, MI, 48128

Zissimos P. Mourelatos

Professor, Mechanical Engineering Department, Oakland University, Engineering Center, Room 402D, 115 Library Drive; Rochester, MI, 48309

1Corresponding author.

ASME doi:10.1115/1.4040626 History: Received February 10, 2018; Revised June 16, 2018


Testing of components at higher-than-nominal stress level provides an effective way of reducing the required testing effort for system reliability assessment. Due to various reasons, not all components are directly testable in practice. The missing information of untestable components poses significant challenges to the accurate evaluation of system reliability. This paper proposes a sequential accelerated life testing (SALT) design framework for system reliability assessment of systems with untestable components. In the proposed framework, system-level tests are employed in conjunction with component-level tests to effectively reduce the uncertainty in the system reliability evaluation. To minimize the number of system-level tests which are much more expensive than the component-level tests, the accelerated life testing design is performed sequentially. In each design cycle, testing resources are allocated to component-level or system-level tests according to the uncertainty analysis from system reliability evaluation. The component-level or system-level testing information obtained from the optimized testing plans are then aggregated to obtain the overall system reliability estimate using Bayesian methods. The aggregation of component-level and system-level testing information allows for an effective uncertainty reduction in the system reliability evaluation. Results of two numerical examples demonstrate the effectiveness of the proposed method.

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