An Improved Approach to Production Planning in Oil Sands Mining Through Detailed Analysis and Simulation of Cycle Times

• Author / Creator

  Goris Cervantes, Eduardo

• The objective of this thesis is to develop, implement and verify a theoretical framework based on detailed analyses and simulation of truck and shovel cycle times in open pit mining, placing an emphasis on the hauling component of the cycle. The goal is to improve the generation of accurate and reliable cycle time estimates to aid in the production planning stages and ongoing performance evaluation. The literature review showed that there is a void in this area of research. In order to achieve this, analyses on a major oil sands operation in Northern Alberta were performed, identifying the source of variability within the cycle time as the truck hauling component. The shortcomings of current commercially available estimating tools are mostly attributed to their overly simplistic assumptions in using truck manufacturers’ performance data, which indicated operating parameters under ideal conditions that are not indicative of those in practice. In addition, most digital models of mine haul road networks are overly simplistic and lack detail. The main factors affecting the performance of the haul trucks are over or under loading (payload variability), total resistance due to gradients and road conditions, and other hindrances in the haulage such as traffic interactions. This framework introduces two methods for producing cycle time estimates; one that mimics the currently available software packages which solely use manufacturer-supplied data and serves as a benchmark, and another method that is probabilistic and historical data-driven. The main data requirements are outlined, and include a detailed model of the mine’s road network, dispatch production records, truck velocity data and other operational parameters such as operating guidelines and rolling resistance values. The concept of EFH is introduced due to a need to categorize different haul routes of equal distances based on how inclined or declined they are, and how rolling resistance varies; which affect truck performance. A computer program was generated using MATLAB, and the algorithm is thoroughly explained. Efforts were made to ensure the flexibility and wide-ranging applicability of this framework to other mining operations. A case study is presented in order to validate the model, and a more advanced application of this new approach is displayed. The data acquisition activities for the mine in the case study are outlined. The framework is validated on four haulage profiles of varying lengths, showing accurate predictions of cycle times. The more advanced application of the framework shown in the case study consists of a productivity and production rate estimate for a period of three months at the oil sands operation. The results are compared to the database in order to assess the framework’s prediction accuracy, and to the old method adopted by the staff at the mine to show the superiority of this approach. This framework generates TPGOH productivity estimates that are within 0.1% accuracy of the database records, while the old method generated estimates that were up to 18% off. Due to the probabilistic nature of this simulation method, several replications are run. The program in this thesis is found to achieve desired accuracy and confidence levels for complex scenarios in a matter of seconds. Using EFH, a planning tool similar to the old method is produced, and yields results with an error of less than 4%. Recommendations for future work are provided, and center around two topics: properly characterizing the details of mine advancement within bench faces and movement of dump locations, as well as properly characterizing the dispatch logic in order to be able to correctly predict empty truck travel times.

• Subjects / Keywords

  • Cycle Time
  • Mine Planning
  • Productivity
  • Simulation
  • Open Pit
  • Life-Of-Mine
  • Optimization
  • Mining
  • Engineering

• Graduation date

  Fall 2018

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R3XW48C2X

• License

  Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.