Economic Efficiency of Centralized Maintenance and Servicing of Technological Vehicles in Iron Ore Quarries

Abstract

The study substantiates and formalizes the criterion for determining the optimal level of centralization in performing routine maintenance and technical servicing of technological vehicles at iron ore quarries. The forms of functional relationships were established, and analytical dependencies were obtained between the costs of maintenance and repair of quarry dump trucks. The relationship between machine reliability and operating time necessary to meet the technological transport plan for ore was determined for cases where such repairs are performed in-house or through company-based or service maintenance at specialized enterprises using industrial methods. This approach allows determining the level of industry-wide centralization of maintenance and repair work for quarry vehicles, which enables minimizing specific operational costs per unit of transport work.

To solve the tasks set, methods of techno-economic, correlation-regression, factor, and situational analysis were used (for studying the organization of dump truck repairs at mining enterprises or in the network of service centers); the methodology of optimal management, which ensures the economic-mathematical formalization of the components of the model for determining the level of industry centralization of technological vehicle repairs according to operating conditions; and the method of comparative economic analysis (for assessing the economic efficiency of the proposed model for reallocating funds allocated to restore the operability of quarry dump trucks).

The optimal level of centralization of maintenance and repairs of 130-ton quarry dump trucks for ore transportation at iron ore quarries was calculated, and the feasibility of ensuring their planned operating time in technological transportation was substantiated.

Keywords: transport system of an iron ore quarry, repair costs, in-house repairs, repairs by specialized organizations, statistical methods of control and management.