Seyed Javad Hosseini Kiasari - Faculty of mining, petroleum and geophysics, Shahrood University of technology, Iran
Sadjad Mohammadi Ivatloo - Faculty of mining, petroleum and geophysics, Shahrood University of technology, Iran
Reza Kakaei - Faculty of mining, petroleum and geophysics, Shahrood University of technology, Iran
Mohammad Ataei - Faculty of mining, petroleum and geophysics, Shahrood University of technology, Iran

Open pit mines have very high economical and operational risk because of high rate of production and using large scale machines. Therefore, it is necessary to assurance the availability of the operational equipment. Nowadays, operation conditions and machines availability can be assessed and analyzed with use of the reliability methods and consequently by carrying out the preventive maintenance scheduling in order to decrease downtimes and costs. This paper aims to model and analyze the reliability of loading machines (shovel) in Sarcheshmeh Copper Mine and to present preventive maintenance scheduling based on the result of reliability modelling. For this purpose, each shovel was considered a subsystem of loading fleet. At first, the failure data have been collected and analyzed. Result showed that two machines 2206 and 2209 are critical machines with regard to the time of failure and number of failure respectivily. Then by using probability method and conducting serial correlation and trend test, best fit distribution and the reliability model for each machine has been determined. In the next step, the reliability of loading fleet has been determined by considering the parallel configuration of subsystems. The results showed the reliability of loading fleet reached to 50% after 100 hours of operation. In addition, it reduces to 20%, approximately 200 hours. Finally preventive reliability-based maintenance for machines at 80% reliability has been suggested 7, 14 and 21 hour time intervals. With the use of this preventive maintenance, the reliability of loading fleet has always remained at the level of greater than 99%.

Maintenance scheduling, reliability, open pit mines, loading machines, Sarcheshmeh copper mine