24-MMP-A5 Surface Mining Methods and Design · May 2014
Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)
EGBC National Exam — Mining and Mineral Processing Engineering, 09-MMP-A5 Surface Mining Methods and Design, 2014-May. 3 hours duration, closed book; one hand-written 8.5×11 inch reference sheet and an approved Casio or Sharp calculator permitted. Question 1 is compulsory (40 marks, all six parts 1.1–1.6); a candidate then selects THREE of Questions 2–6 (each worth 20 marks).
Reference texts: Hartman & Mutmansky (eds.), SME Mining Engineering Handbook, 3rd ed. (dragline stripping systems, truck-shovel productivity, mine cost estimation — the primary reference throughout this paper); Hustrulid, Kuchta & Martin, Open Pit Mine Planning and Design, 3rd ed. (block-model economics, floating/moving-cone algorithm, the Lerchs–Grossmann graph-theoretic pit-optimization method, annual push-back scheduling); Kennedy, B.A. (ed.), Surface Mining, 2nd ed., SME (dragline range-diagram geometry, stripping methods); Lerchs, H. & Grossmann, I.F. (1965), “Optimum Design of Open-Pit Mines,” CIM Bulletin, 58, 47–54.
Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.
A cost index is a dimensionless ratio, tracked over time against a fixed base year, that scales a known historical cost to an equivalent cost today (or in a future study year) without re-estimating from first principles: Cost year2 = Cost year1 × (Index year2 / Index year1). It is a quick, low-cost way to update an old quotation or a prefeasibility estimate for inflation and input-price drift.
Two indexes commonly used for mining capital/operating costs: (1) the Marshall & Swift (M&S) Equipment Cost Index, a broad North-American industrial-equipment index (weighted mix of machinery, process equipment and installation labour) widely used to escalate mining/mineral-processing plant capital costs; and (2) mining-specific parametric capital-cost indexes published in USBM/CIM cost-estimating handbooks (e.g. the Camm/O’Hara-style category indexes used in Question 3.3 below, or Statistics Canada’s Non-Residential Building/Machinery & Equipment Price Indexes), which track mining-machinery and construction-labour costs specifically rather than general industrial goods.
Problems applying a single index across all cost sectors and jurisdictions: a mine’s cost is a mix of equipment (import/exchange-rate sensitive), labour (regional wage-scale and union-contract sensitive), energy (diesel/electricity, volatile and jurisdiction-specific) and consumables (steel, explosives, tyres — commodity-price driven) — a single blended index cannot track all of these proportionally, so it systematically mis-escalates whichever category is over- or under-represented relative to the index’s own weighting basket. It also does not capture technology change (a modern haul truck is not simply an inflated 1997 truck — it is more productive per dollar), regional cost differentials (freight to remote/northern Canadian sites vs. the index’s usually US-Gulf-Coast or continental-average basis), currency movements between the index’s home currency and the project’s, and non-linear scale effects (bulk-purchase discounts that a linear index cannot reproduce). Indexes are therefore reliable for short escalation periods (a few years) on well-matched cost categories, and unreliable across decades, across countries, or when technology has materially changed since the base estimate.
