Received 08.02.2026
Revised 03.03.2026
Accepted 26.03.2026
Published 07.04.2026
Retrieved from Iss. 119, 2026
Pages 249 -261
Abstract
The increasing complexity of building engineering networks, integration of subsystems with different functional purposes, and growing requirements for uninterrupted operation necessitate the development of a scientifically grounded system of organizational and technological monitoring. Effective management of water supply, heat supply, power supply, and ventilation networks requires a transition from fragmented control of individual parameters to a comprehensive model for quantitative assessment of functional stability. The methodological framework is based on the integration of systemic, functional, and risk-oriented approaches, enabling the analysis of engineering networks as an integrated technical and organizational complex with interrelated elements and a hierarchy of critical parameters. Formalization of monitoring processes is implemented through the construction of an integral stability indicator determined by weighted aggregation of normalized operational parameters, ensuring objectivity in comparative assessment of different network sections. Calculation of the probability of failure-free operation, failure rate, and integral risk makes it possible to transform technical characteristics into measurable economic criteria and to establish priorities for technical intervention. The application of simulation modeling provides scenario-based analysis of operating modes and forecasting of equipment degradation dynamics under variable load conditions. An integral operational efficiency index combining stability indicators, failure probability, and load variability into a unified decision-support system is proposed. Integration of analytical models into a digital information platform forms a comprehensive monitoring loop that enhances operational reliability, reduces accident rates, optimizes maintenance costs, and ensures long-term stability of building engineering network systems under dynamic operating conditions. Practical implementation of the proposed tools contributes to the formation of an adaptive infrastructure management model based on predictability, systemic coordination, and economic feasibility
Keywords:
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