Improved Aggregate Repair Method Based on the Survivability Criterion
Abstract
Purpose. Enhancing the Effectiveness of Combat Readiness Restoration of Weapons and Military Equipment in Combat Operations through an Improved Aggregate Repair Process Based on the Maximization of Survivability.
Method. The study employs an analytical-algorithmic approach that includes damage assessment, evaluation of structural integrity, verification of spare-unit availability, and repair-time forecasting. The obtained data, through combat capability and survivability indices, enable the selection of the most effective sequence of aggregate restoration.
Findings. An improved aggregate repair method has been developed that integrates damage assessment, structural integrity evaluation, spare-unit availability analysis, and repair-time forecasting. This method enhances the operational efficiency of restoring automotive and armored vehicles according to the survivability criterion and reduces inefficient resource expenditures under combat conditions.
Theoretical value of the study. The study establishes an integrated theoretical model of aggregate repair that employs combat capability and survivability coefficients. These coefficients provide a quantitative description of how damage levels affect the recoverability of armored vehicles. The proposed approach deepens the scientific understanding of military equipment survivability and expands the methodological foundations for optimizing repair processes under combat conditions.
Originality / Research value. A new aggregate repair method is proposed that, for the first time, integrates combat capability indices, survivability coefficients, and repair-time prediction into a unified information-based ranking system. This approach enables a scientifically grounded selection of the optimal repair sequence, significantly enhancing the effectiveness of armored vehicle recovery in dynamic combat environments.
Future research. A new aggregate repair method is proposed that, for the first time, integrates combat capability indices, survivability coefficients, and repair-time prediction into a unified information-based ranking system. This approach enables a scientifically grounded selection of the optimal repair sequence, significantly enhancing the effectiveness of armored vehicle recovery in dynamic combat environments.
Paper type. Research article.
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