On one approach to the homogeneity of the statistical estimation of technical systems

Abstract

The article addresses the problem of ensuring the statistical homogeneity of empirical data in the reliability and availability analysis of complex technical systems (CTS). The author proceeds from the thesis that statistics, as the science of homogeneous events, requires a strict identification of common characteristics among research objects, as ignoring this factor leads to coarse and uninformative results. The work draws a parallel between stratification methods in medicine (specifically in gerontology) and the processes of technical operation of aviation and transport fleets. It is substantiated that just as medical statistics account for age-related changes in the body (children, adolescents, elderly), technical evaluation must be based on the dynamic stratification of an object's life cycle to account for irreversible structural changes in materials, metal fatigue, and accumulated wear.

The methodological foundation of the study is the distributive approach, which involves classifying failures according to specific physical degradation processes such as corrosion, vibration, friction, and thermal loading. The author details a graphical model of life cycle stratification, clearly demonstrating the increase in the baseline failure rate even after major overhauls, caused by processes that repair cannot neutralize. Special attention is paid to the extended operation stage where latent failures that are not detected by routine maintenance methods (MS-1, MS-2) become critically important.

The scientific novelty of the work lies in the development and substantiation of a criterion for filtering out anomalous values in a statistical sample to maintain its homogeneity. It is established that exceeding the standard indicates the presence of hidden defects, requiring the exclusion of such events from the general calculation of reliability indicators.

In the final part of the article, the author proposes using the availability factor k_ТВ and the coefficient of technical utilization k_г as tools for quantitative efficiency assessment across four intervals: before the first overhaul, between repair cycles, until decommissioning, and at the "life extension" stage after the expiration of the designated service life. The proposed approach enables a transition from averaged reliability estimates of the entire fleet to individual technical condition monitoring for each unit of the CTS, ensuring high predictive accuracy.