A. Nouri Qarahasanlou; M. Ataei; R. Shakoor Shahabi
Abstract
Whether directly in the form of expenses or indirectly, the objective of maintenance in the mining industry is self-evident in time losses and loss of production. In this paper, the reliability-based maintenance is examined with a different insight than before. The system goes back to the Good As New ...
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Whether directly in the form of expenses or indirectly, the objective of maintenance in the mining industry is self-evident in time losses and loss of production. In this paper, the reliability-based maintenance is examined with a different insight than before. The system goes back to the Good As New (GAN) state or too Bad As Old (BAO) maintenance state; why so, the maintenance of the system shifts to the midrange state. On the other hand, the implementation of repairs is strongly influenced by the environmental factors that are known as the “risk factors”. Therefore, an analysis requires a model that integrates two basic elements: (1) incompleteness of the maintenance effect and (2) risk factors. Thus, an extensive proportional hazard ratio model (EPHM) is used as a combination of the Proportional Hazard Model (PHM) and the Hybrid Imperfect Preventive Maintenance model (HIPM) in order to analyze these elements. In this regards, four different preventive maintenance strategies are proposed. All four strategies are time-based including constant interval or periodic (the first and second strategies) and cyclic interval (the third and fourth strategies). The proposed method is applied for a Komatsu HD785-5 dump-truck in the Songun copper mine as a case study. The PM intervals with a mean value of risk factors for the four activities to reach the 80% reliability for the first and second strategies are about 5 and 48 hours. These intervals for the third strategy are calculated as 48.36, 11.58, 10.25, and 9.035, and for the fourth strategy are 5.06, 4.078, 3.459, and 1.92.
Exploitation
R. Razzaghzadeh; R. Shakoor Shahabi; A. Nouri Qarahasanlou
Abstract
The appropriate operating of mining machines is affected by both the executive and environmental factors. Considering the effects and the related risks lead to a better understanding of the failures of such machines. This leads to a proper prediction of the reliability parameters of such machines. In ...
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The appropriate operating of mining machines is affected by both the executive and environmental factors. Considering the effects and the related risks lead to a better understanding of the failures of such machines. This leads to a proper prediction of the reliability parameters of such machines. In this research work, the reliability and maintainability analysis of the loading and haulage machines in the Sungun Copper Mine, considering the repair condition as multiple repairable units, was performed. For this purpose, the data necessary for the loading and haulage equipment including 2 loaders and 8 dump trucks for a 15-month period was collected and categorized in 10 operational units after the system and sub-systems of the department were determined. Initially, the time between failures (TBFs) and time to repair (TTR) for each unit was calculated. Then 20 sub-systems were developed. Primarily, the Stata software was utilized to carry out the heterogeneity test for all the sub-systems. In consequence, most of the sub-systems were regarded as the heterogeneous ones, except for 7 of them including the dump truck units 1, 2, 3, 4, 5, 7, and 8 in TBFs. Hence, "PHM" that is a covariate-based model displayed the heterogeneous group. Its reliability function was also estimated. For the next step, the trend tests were done on the non-heterogeneous sub-systems by means of the Minitab software. The homogeneous sub-systems with failure trend were modeled by “NHPP”. Afterwards, the non-trended sub-systems formed the data group. Later, the correlation tests were modeled by “HPP”. Finally, the reliability and maintainability functions were calculated with the 95% confidence level.