Simulating Fréchet Distribution Under Multiply Censored Partially Accelerated Life Testing

Showkat Ahmad Lone ()
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Showkat Ahmad Lone: Saudi Electronic University

Annals of Data Science, 2023, vol. 10, issue 6, No 1, 1447-1458

Abstract: Abstract Accelerated life testing has now become the primary method for rapidly assessing product reliability and designing efficient test plans is a vital step in ensuring that accelerated life tests can properly, quickly, and economically assess product reliability. These tests subject the sample to high levels of stress. Then, based on the stress-life relationship, the product life at a normal stress level can be calculated by extrapolating the life information from a sample at a high-stress level to the normal level. The purpose of the study is to investigate the estimation of failure time data for step-stress partially accelerated life testing using multiply censored data. The test components’ lifetime distribution is assumed to follow Fréchet’s distribution. The distribution parameter and tampering coefficient are estimated using maximum-likelihood point and interval estimations. A Monte Carlo simulation study is used to evaluate and compare the performance of model parameter estimators utilizing multiply censored data in terms of biases and root mean squared errors.

Keywords: Fréchet distribution; Maximum likelihood estimation; Multiply censored data; Partially accelerated life test; Simulation study; Acceleration factor (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s40745-022-00399-4

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