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A reliability model for non-isothermal isotropic damages
Un modelo de confiabilidad para daños isotrópicos no isotérmicos
DOI:
https://doi.org/10.15446/dyna.v91n232.111320Keywords:
reliability; Neyman type A distribution; accelerated life tests (en)confiabilidad; distribución de Neyman tipo A; pruebas de vida aceleradas (es)
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This study introduces a novel lifetime distribution originating from the Neyman Type A distribution. We built a Neyman Type A counting process and developed a survival function. Some statistical properties of the new distribution were presented, such as the resulting humped hazard function and its convergence. An accelerated test model structure with Arrhenius law was specified, and the effects of different accelerating stresses were analyzed. The hazard function implied by the model is inversely proportional to the stress, which results in interesting features and provides an efficient approach to describe the lifespan phenomena of some engineering metals and bulbs under low temperatures. The estimation of parameters of the accelerated model by maximum likelihood, mean time to failure, and expected number of failures are discussed in the numerical experiments.
Este artículo presenta una nueva distribución de vida útil que se origina a partir de la distribución de Neyman Tipo A. Construimos el proceso de conteo de Neyman Tipo A y desarrollamos la función de supervivencia. Se presentan algunas propiedades estadísticas de la nueva distribución, como la función de riesgo resultante en forma de joroba y su convergencia. Se especifica una estructura de modelo de prueba acelerada con la ley de Arrhenius, y se analizan los efectos de diferentes tensiones acelerantes. La función de riesgo implicada por el modelo es inversamente proporcional al estrés, lo que resulta en características interesantes: el modelo proporciona un enfoque eficiente para describir los fenómenos de vida útil de algunos metales de ingeniería y bombillas a bajas temperaturas. Se discute la estimación de parámetros del modelo acelerado mediante máxima verosimilitud, el tiempo medio hasta la falla y el número esperado de fallas en experimentos numéricos.
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