The paper provides an overview of the principal failure rate distributions and it is focused on the comparison between exponential and Weibull distributions: this study illustrates the advantages and disadvantages of the constant failure rate of the exponential distribution and the Weibull time-dependent behavior. The second part of the paper deals with the parameter estimation methods that used to determine the best-fitting distribution for a set of data collected during testing or field operations. The methods considered in that case are probability plotting, Least Square Estimation and Maximum Likelihood Estimation. Finally, two different types of field data such as failure times achieved with testing of electronic board for avionics components are analyzed by software to find which distribution fits better the data.

Application and analysis of methods for the evaluation of failure rate distribution parameters for avionics components / Ciani, Lorenzo*; Guidi, Giulia. - In: MEASUREMENT. - ISSN 0263-2241. - ELETTRONICO. - 139:(2019), pp. 258-269. [10.1016/j.measurement.2019.02.082]

Application and analysis of methods for the evaluation of failure rate distribution parameters for avionics components

Ciani, Lorenzo
;
GUIDI, GIULIA
2019

Abstract

The paper provides an overview of the principal failure rate distributions and it is focused on the comparison between exponential and Weibull distributions: this study illustrates the advantages and disadvantages of the constant failure rate of the exponential distribution and the Weibull time-dependent behavior. The second part of the paper deals with the parameter estimation methods that used to determine the best-fitting distribution for a set of data collected during testing or field operations. The methods considered in that case are probability plotting, Least Square Estimation and Maximum Likelihood Estimation. Finally, two different types of field data such as failure times achieved with testing of electronic board for avionics components are analyzed by software to find which distribution fits better the data.
2019
139
258
269
Ciani, Lorenzo*; Guidi, Giulia
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1153449
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