UBC Theses and Dissertations
Capital investment appraisal for advanced mining technology : case studies in GPS and information based surface mining technology Dessureault, Sean
Canadian, American and Australian mining industries are currently faced with the requirement to streamline their operations in light of new economic realities. Automation has been seen as a key step toward the survival and competitiveness of these industries. Unfortunately, technology providers seldom have the expertise or resources to properly transfer technology from the development stage to the productive stage. Mining companies, the potential customers of technology providers are similarly inexperienced at appraising and implementing these new technologies. The manufacturing industry is well experienced in appraising (referred most commonly in manufacturing as justifying) and implementing new technology and has developed numerous capital investment appraisal (CIA) methods that can more accurately appraise new technology. These techniques offer the potential to be adapted to suit the mining industry. The primary objective of this thesis is to investigate the usefulness of various decisionmaking tools in the CIA of advanced technologies for the mining industry. This research discusses the current technological situation in the mining industry to show the requirement for new capital appraisal techniques. The current evaluation methods are analyzed and their weaknesses are identified. The classification schemes and CIA methods derived from the manufacturing industry are adapted to mining. Analytical examples are provided in terms of hypothetical situations and two case studies at an open pit copper mine in British Columbia are described. The first case study reveals the limitations of current CIA methods when applied to advanced technology and applies alternative CIA techniques whose applicability is rated by the decision-maker at the mine as being "very useful". The second case study uses object based simulation as a CIA tool for a blending project by estimating parameters within the project that were previously only subjective opinion.
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