Analysis of the Application of Continuous Distribution Laws in the Reliability Theory of Technical Systems : a Review Article
Year: 2025
Type: conference-paper
Abstract: In order to enhance the accuracy of reliability assessments for highly reliable and low-volume technical systems, it is essential to utilise diverse prior information obtained through reliability calculations, simulations, testing, and operational data from structurally similar systems (analogues). From a systems approach perspective, any reliability study of technical systems should be planned and conducted considering results from previous research, i.e., incorporating prior information. Given the stochastic nature of reliability, which is an inherent property of technical systems, various discrete and continuous distributions can be employed as theoretical distributions for reliability metrics. This article analyses the practical application of key continuous probability distributions in the reliability theory of technical systems. The article presents dependencies for estimating primary reliability metrics and highlights their specific applications under different conditions. The analysis is based on a systematisation of information published in scientific and technical literature, including results from model-based and experimental reliability studies, as well as operational statistical data. The provided analytical research was carried out under a project on the prototype development of a retractable rotor system for a convertiplane. It involved making design changes to the completed technical system, which required a comprehensive assessment of reliability parameter changes at initial development stages. The results obtained allow for improving the efficiency of building models and criteria for ensuring and controlling the reliability of a convertiplane, while simultaneously increasing the accuracy of reliability estimates.
DOI: 10.25673/123103
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7155199839