Rustamov K.J., Atabaev G.G., Khodjaeva Sh.M.
Tashkent State Transport University, Uzbekistan

Abstract. The article presents a methodological approach to modeling the rational periodicity of maintenance for excavators in order to enhance their operational efficiency and reduce overall life-cycle costs. A comprehensive analysis of the technical condition, workload intensity, and operating environment of excavators has been performed to determine the optimal maintenance intervals. The proposed model integrates economic, reliability, and operational parameters, allowing for a quantitative evaluation of maintenance efficiency and downtime minimization. Using analytical and simulation methods, the dependence between maintenance frequency and operational performance indicators has been established. The study results demonstrate that the rational selection of maintenance periodicity contributes to a 10–15% reduction in energy and resource consumption while increasing machine availability and service life. The developed economic-mathematical model can serve as a basis for improving maintenance planning strategies in construction and mining machinery, ensuring sustainable and costeffective technical operation.

Keywords: Excavator, maintenance periodicity, operational efficiency, reliability, optimization, economic model, simulation, life-cycle cost, downtime, hydraulic system, technical operation, energy efficiency.

Introduction: 
    The continuous growth of mechanization and automation in construction, mining, and road-building industries has increased the operational demand for excavators, which are among the most widely used technological machines in the world. Excavators perform complex cycles of digging, lifting, swinging, and dumping, and their operational efficiency directly affects the overall productivity, energy consumption, and cost-effectiveness of technological processes. Ensuring high operational efficiency and reliability of such machines, therefore, becomes a key objective in modern engineering practice and machine operation management.
    Under real-world conditions, excavators are exposed to fluctuating dynamic loads, harsh environmental influences, and irregular work cycles. These conditions accelerate the wear of key hydraulic, mechanical, and transmission components, which in turn affects the reliability and stability of performance. The hydraulic drive systems, which constitute the energy core of the machine, are particularly sensitive to overloads, temperature variations, and contamination. As a result, the technical condition of these systems directly determines the fuel and energy consumption, working speed, and overall functional efficiency of excavators.
    To maintain the required performance and minimize unplanned downtime, regular maintenance activities are performed throughout the machine’s life cycle. However, in many enterprises, maintenance periodicity is still based on rigid manufacturer recommendations or outdated standards that do not consider the actual operating conditions, usage intensity, or environmental variability. Consequently, two types of inefficiencies occur: (1) over-maintenance, which increases maintenance costs and unnecessary downtime, and (2) under-maintenance, which leads to premature failures and loss of productivity. This imbalance highlights the urgent need for a scientifically grounded approach to defining rational maintenance intervals that balance reliability, cost, and operational efficiency
    The objective of this research is to develop an economic–mathematical model that determines the rational periodicity of maintenance for excavators based on real operating conditions. The model integrates parameters such as reliability indices, energy consumption, hydraulic system performance, and maintenance costs. Through analytical modeling, experimental validation, and simulation analysis, the study seeks to establish an optimal maintenance schedule that ensures maximum availability, minimal downtime, and extended machine service life. The results of this research are expected to contribute to the development of an adaptive maintenance planning methodology applicable to both construction and mining machinery, supporting the transition toward sustainable, energy-efficient operation in the industrial sector.