One of the surface mining methods is open-pit mining,by which a pit is dug to extract ore or waste downwards from the earth’s surface.In the mining industry,one of the most significant difficulties is long-term produ...One of the surface mining methods is open-pit mining,by which a pit is dug to extract ore or waste downwards from the earth’s surface.In the mining industry,one of the most significant difficulties is long-term production scheduling(LTPS)of the open-pit mines.Deterministic and uncertainty-based approaches are identified as the main strategies,which have been widely used to cope with this problem.Within the last few years,many researchers have highly considered a new computational type,which is less costly,i.e.,meta-heuristic methods,so as to solve the mine design and production scheduling problem.Although the optimality of the final solution cannot be guaranteed,they are able to produce sufficiently good solutions with relatively less computational costs.In the present paper,two hybrid models between augmented Lagrangian relaxation(ALR)and a particle swarm optimization(PSO)and ALR and bat algorithm(BA)are suggested so that the LTPS problem is solved under the condition of grade uncertainty.It is suggested to carry out the ALR method on the LTPS problem to improve its performance and accelerate the convergence.Moreover,the Lagrangian coefficients are updated by using PSO and BA.The presented models have been compared with the outcomes of the ALR-genetic algorithm,the ALR-traditional sub-gradient method,and the conventional method without using the Lagrangian approach.The results indicated that the ALR is considered a more efficient approach which can solve a large-scale problem and make a valid solution.Hence,it is more effectual than the conventional method.Furthermore,the time and cost of computation are diminished by the proposed hybrid strategies.The CPU time using the ALR-BA method is about 7.4%higher than the ALR-PSO approach.展开更多
Equipment plays an important role in open pit mining industry and its cost competence at efficient operation and maintenance techniques centered on reliability can lead to significant cost reduction.The application of...Equipment plays an important role in open pit mining industry and its cost competence at efficient operation and maintenance techniques centered on reliability can lead to significant cost reduction.The application of optimal maintenance process was investigated for minimizing the equipment breakdowns and downtimes in Sungun Copper Mine.It results in the improved efficiency and productivity of the equipment and lowered expenses as well as the increased profit margin.The field operating data of 10 trucks are used to estimate the failure and maintenance profile for each component,and modeling and simulation are accomplished by using reliability block diagram method.Trend analysis was then conducted to select proper probabilistic model for maintenance profile.Then reliability of the system was evaluated and importance of each component was computed by weighted importance measure method.This analysis led to identify the items with critical impact on availability of overall equipment in order to prioritize improvement decisions.Later,the availability of trucks was evaluated using Monte Carlo simulation and it is revealed that the uptime of the trucks is around 11000 h at 12000 operation hours.Finally,uncertainty analysis was performed to account for the uncertainty sources in data and models.展开更多
文摘One of the surface mining methods is open-pit mining,by which a pit is dug to extract ore or waste downwards from the earth’s surface.In the mining industry,one of the most significant difficulties is long-term production scheduling(LTPS)of the open-pit mines.Deterministic and uncertainty-based approaches are identified as the main strategies,which have been widely used to cope with this problem.Within the last few years,many researchers have highly considered a new computational type,which is less costly,i.e.,meta-heuristic methods,so as to solve the mine design and production scheduling problem.Although the optimality of the final solution cannot be guaranteed,they are able to produce sufficiently good solutions with relatively less computational costs.In the present paper,two hybrid models between augmented Lagrangian relaxation(ALR)and a particle swarm optimization(PSO)and ALR and bat algorithm(BA)are suggested so that the LTPS problem is solved under the condition of grade uncertainty.It is suggested to carry out the ALR method on the LTPS problem to improve its performance and accelerate the convergence.Moreover,the Lagrangian coefficients are updated by using PSO and BA.The presented models have been compared with the outcomes of the ALR-genetic algorithm,the ALR-traditional sub-gradient method,and the conventional method without using the Lagrangian approach.The results indicated that the ALR is considered a more efficient approach which can solve a large-scale problem and make a valid solution.Hence,it is more effectual than the conventional method.Furthermore,the time and cost of computation are diminished by the proposed hybrid strategies.The CPU time using the ALR-BA method is about 7.4%higher than the ALR-PSO approach.
基金the support of the Maintenance Department of Mobin Co.Sungun Copper mine
文摘Equipment plays an important role in open pit mining industry and its cost competence at efficient operation and maintenance techniques centered on reliability can lead to significant cost reduction.The application of optimal maintenance process was investigated for minimizing the equipment breakdowns and downtimes in Sungun Copper Mine.It results in the improved efficiency and productivity of the equipment and lowered expenses as well as the increased profit margin.The field operating data of 10 trucks are used to estimate the failure and maintenance profile for each component,and modeling and simulation are accomplished by using reliability block diagram method.Trend analysis was then conducted to select proper probabilistic model for maintenance profile.Then reliability of the system was evaluated and importance of each component was computed by weighted importance measure method.This analysis led to identify the items with critical impact on availability of overall equipment in order to prioritize improvement decisions.Later,the availability of trucks was evaluated using Monte Carlo simulation and it is revealed that the uptime of the trucks is around 11000 h at 12000 operation hours.Finally,uncertainty analysis was performed to account for the uncertainty sources in data and models.
