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Adaptive Design and Inference for Step-Stress Accelerated Life Testing

Abstract Number:

903 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Paper 

Participants:

David Han (1), Haifa Ismail-Aldayeh (1)

Institutions:

(1) University of Texas at San Antonio, N/A

Co-Author:

Haifa Ismail-Aldayeh  
University of Texas at San Antonio

First Author:

David Han  
University of Texas at San Antonio

Presenting Author:

David Han  
University of Texas at San Antonio

Abstract Text:

The adaptive step-stress accelerated life test (ada-ssALT) was developed to address several practical shortcomings of the conventional simple step-stress ALT (ssALT). While ada-ssALT demonstrates superior performance over ssALT in terms of estimate bias and precision, particularly when the lifetime of experimental units follows an exponential distribution, the constant hazard function of the exponential model restricts its applicability in real-world scenarios. To overcome this limitation, the log-location-scale family, which includes widely used distributions such as Weibull, log-normal, and log-logistic, provides greater flexibility through the incorporation of a shape parameter. This study extends ada-ssALT to a generalized form, allowing the test unit's lifetime at each stress level to follow a log-location-scale distribution. Here we present the model formulation, maximum likelihood estimation, and derivation of the information matrix, assuming a linear relationship between the standardized stress level and the location parameter. A simulation study compares the performance of ada-ssALT with ssALT across various design criteria.

Keywords:

accelerated life tests|adaptive design|Fisher information|maximum likelihood estimator|step-stress loading|Type-I censoring

Sponsors:

Quality and Productivity Section

Tracks:

Reliability and Life Testing

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