Reliability analysis of full-face tunnel boring machines by Monte Carlo simulation technique
Keywords:Reliability, Monte Carlo simulation, tunnel boring machine, preventive maintenance
AbstractThe high boring capability of full-face tunnel boring machines, especially in urban tunnels, has led to their increasing use in tunnel excavation in various and unfavourable geological conditions. Therefore, many efforts have been made to predict and improve the performance of these machines. In this regard, most of the previous studies have focused on the effect of geological and mechanical properties of rock or soil. However, delays due to the maintenance and repair of these machines, which contribute a major share of unwanted and unpredicted stops at work, have not been considered. Reliability analysis is a practical method based on studying the behaviour of breakdowns and maintenance of machines and systems. This approach can be suggested as appropriate planning for machine maintenance and consequently reducing downtime and costs. In this way, it is possible to identify weaknesses and critical points of a machine or system of the boring process. In the present study, the reliability of the full-face tunnelling machine was analysed by the Monte Carlo simulation method. The studied machine is divided into 5 subsystems including mechanical, electrical, hydraulic, water and compressed air subsystems. Using breakdown data of about 24 months of boring operation, the reliability of each subsystem was simulated and evaluated. Eventually, the reliability of the boring machine was simulated using the Kamat-Riley (K-R) method. The results showed that if no maintenance operation is performed on the subsystems, the overall reliability of the boring machine will decline to zero after about 38 hours of continuous boring operation. Finally, to improve the overall reliability of the boring machine, based on accomplished reliability analysis, we suggest effective preventive maintenance and repair system for keeping the machine in optimal operating conditions for a longer period.
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