Optimization and simulation-based verification of near face stockpile mining method

• Author / Creator

  Gong, Hongshuo

• The downturn of the world economy and the increasingly severe competition among mining giants puts forward higher requirements for open-pit mining, which is the dominant method for humans to obtain minerals from the earth. Among these so-called higher requirements, reducing mining costs as much as possible is the most important one. Only by reducing mining costs can the profit margin of the enterprise be improved, so that the enterprise can survive the fierce market competition. Fundamentally speaking, there are two main ways to reduce mining costs. The first is to increase the utilization rate of existing equipment under existing conditions, that is, to achieve the expected benefits by formulating efficient long-term, medium- and short-term plans. The other is to improve the current mining methods. This needs to improve the deficiencies of the existing conventional mining methods from the system level to further improve production efficiency. Near face stockpile mining method is an innovative open-pit mining method based on this condition. Compared with traditional mining methods, this method creatively uses the approach of the in-pit-near-crusher stockpile to isolate or decouple the mining process from the crushing and processing process, so as to minimize the problem of low equipment utilization caused by mutual influence between the two procedures.
  Several models and algorithms have been put forward to reduce the operational cost by using the first approach but not all major concerns are satisfied, and the results are not optimally guaranteed. Meanwhile, there is no model has been published for the second approach. Therefore, the problem to be addressed in this research is:
  Can a simulation-optimization framework be developed for near face stockpile mining method that (1) generates an optimal or near-optimal schedule, and (2) captures mining and processing operations’ uncertainties, to measure its performance quantitively and compare it with regular out-of-pit mining method?
  The following tasks are going to be considered in this research: (i) to establish, implement and verify a theoretical optimization model for near face stockpile method mining schedule generating while considering multiple practical constraints, (ii) to establish, implement and verify a simulation model that could accurately capture the characteristics of the near face stockpile method, (iii) integrate the optimization model and simulation model and validate the integrated framework and use it to quantitively evaluate the performance of near face stockpile method. To satisfy those tasks listed, the following procedures would be applied: (i) establish a mathematical model for mining schedule optimization, (ii) translate the math model into MATLAB by coding, (iii) verify the mathematical model by case study, (iv) develop simulation model by discrete event simulation software, (v) test and verify the simulation model, (vi) integrate the mathematical model and simulation model into a comprehensive framework, (vii) test and verify the integrated framework, (viii) validate the integrated framework by case study, and (ix) compare the simulated results of near face stockpile method against traditional simulation results and evaluate its performance.
  The main scientific contribution of this study would be: (i) establish a mathematical optimization model that can generate optimal or near-optimal mining schedule for near face stockpile method with limited human intervention, (ii) propose a simulation model that can capture mining and processing operations’ uncertainties of near face stockpile mining method, (iii) develop a comprehensive simulation-optimization framework that can be used to quantitatively measure the performance of different mining methods from multiple aspects.

• Subjects / Keywords

  • Near face stockpile
  • Simulation
  • Optimization

• Graduation date

  Fall 2023

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/r3-1r9k-0766

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.