Systems and Means of Informatics

2026, Volume 36, Issue 3, pp 150-171

INTERPRETABLE STATISTICAL MODELING OF DOCUMENTATION QUALITY AND ITS TEMPORAL DYNAMICS

  • A. A. Sachko
  • A. M. Sachko
  • V. Yu. Pozdyshev

Abstract

Documentation quality at specialized industrial enterprises is a critical factor influencing order lead times, manufacturing process stability, production costs, and product performance. However, existing documentation control approaches primarily focus on identifying already manifested nonconformities and underutilize statistical analysis methods for management decision support, particularly in pattern recognition and risk forecasting. This study aims to develop and validate a statistical analysis methodology for documentation quality to enhance decision support systems at specialized industrial enterprises. The study is based on a comprehensive census of 6,739 documents that underwent standard compliance control (normative control) at a defense industrial enterprise over 12 quarters from Q1 2023 to Q4 2025. These documents were categorized into four types (engineering, software, and graphical documentation, along with change notices) and three quality levels ("Good," "Average," and "Poor"). The research methods included contingency table analysis (Pearson's x2 test, Cramers's V, and standardized residuals) with bootstrap estimation for result robustness; time- trend modeling of the logit-transformed proportion of high-quality documents with residual diagnostics (Shapiro-Wilk, Breusch-Pagan, and Durbin-Watson tests) and forecasting; the Chow test for structural break detection; analysis of covariance (ANCOVA); seasonality analysis; and correlation analysis.

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