COST ESTIMATION IN MINING: THE EVOLUTION OF QUICK EVALUATION METHODS

Transcription

1 COST ESTIMATION IN MINING: THE EVOLUTION OF QUICK EVALUATION METHODS

2 AUTHORS J. Gavronski*, C. Petter** and B. Escobar 1, R. D Arrigo 2 Universidade Federal do Rio Grande do Sul 1 Av. Bento Gonçalves 9500 Porto Alegre, Brazil (Corresponding Author: Jorge.Gavronski@ufrgs.br* ; **cpetter@ufrgs.br) Programa de Pós-Graduação em Engenharia de Minas, Metalúrgica e de Materiais 2 Av. Bento Gonçalves, 9500 Setor 4 - Prédio 74 - Sala 211 Porto Alegre, Brazil

3 Objective Present "Quick Evaluations in mine projects. Discusses in a special way the use of techniques originally proposed by O'Hara. Report the MAFMINE software.

4 Summary Characteristics mining projects Precision mining studies at different stages Quick evaluations (comparison and parametric methods) O Hara model MAFMINE Some results obtained with MAFMINE Conclusion

5 Characteristics mining projects New investments involving many uncertain, reserve, technological characterization of the ore, economic and political factors. Rely on large amounts of resources and have long maturation periods. It is an iterative process. Highlight the necessity to periodically evaluate projects from a technical and economic point of view.

6 Why quick evaluation? The decision to start or continue investing time and resources needs to be revised in light of new information that will be aggregated. It is necessary to confirm at every stage whether the project should continue or be paralyzed. May confirm the whether or not to continue more demanding studies and project implementation. A mining project is started after evaluation mineral reserves create interest.

7 Precision mining studies at different stages Project Phase Conceptual Pre-Feasability Feasability Detailed Study % Engineering Concluded Precision (%) ± ± 5 Reynolds,1990

8 Conceptual engineering project Corresponds to a phase which is very preliminary. No proper engineering studies exist and the calculated costs reflect only the order of magnitude expected.

9 Quick evaluations Constitutes a tool to assist in early design phase. There are several published articles based on empirical formulas of actual operating statistics. Usually these papers indicate the cost of acquisition and operation according to particular type and size of equipment or installation.

10 Example - QUICK EVALUATIONS Cost 1/Cost 2 = (Capacity 1/Capacity 2) 0,6 This simple rule compares the investment that should be analyzed for a stipulated production capacity, with another known and existing investment of similar operation. Considers the relationship between costs is proportional to the high capacity ratio in the exponent 0.6

11 Quick evaluations based on Comparison Method Comparison of similar projects with adjustments to balance differences. The background information includes: listing of operations, supplies and equipment, deposit information, and proposed development. Examples: Proposed by Stebbins and Schumacher (SME chapter 4.8) Cost Estimating for Underground Mines. "Mine and Mill Equipment Costs - An Estimator's Guide, Western Mine Engineering Inc" (2015).

12 Quick evaluations - Parametric Methods Estimate derived costs through generalized algorithms. Most present the following relationship: "Cost = x (parameter)y". The variable can represent: Length, mass, production rate.. x and y are values derived from known data of statistical evaluations or estimated from field operations. Examples of this methodology may be found in the U. S. Bureau of Mining Cost Estimating System (CES USBM 1987) and the O'Hara Model (1980).

13 Example of parametric estimation method Costs are calculated from general algorithms by the following relation: Cooo = cccct (TTT) y Cost Tpd 13

14 Parametric method - Quick evaluations Proposes costs derived from general parameterization algorithms. T. Alan O'Hara developed mathematical models to estimate mining costs (CAPEX and OPEX). From O'Hara s formulas Modele d'analyse Financière - developed at the Centre of GEOTECHNIQUE et d'exploitation du Sous-sol, (Ecole des Mines de Paris). MAFMO software

15 Example - O Hara Model Pre-stripping cost: Validity interval: (TT) from to t. Alterated rock or soft rock C = FFFFFF 1245 TT 0,5 Hard rock: C = FFFFFF TT 0,5 where TT(t) is the pre-stripping tonnage.

16 Price Indexation C = FFFFFF iiiii TT 0,5 Faaaaa iiiii = FFFFoo α FFFFFF β Faaaaa α = (managment, time) Producer Price Index Faaaaa β = (economic local) Big Mac Index 16

17 Main inputs for CAPEX (O Hara Model ) Daily ore production for underground mine and processing plant Daily ore + waste production for open pit mine Pre-stripping tonnage for open pit mine Size of equipement for open pit mine Size of stopes for underground mine Type of access Depth Hoisting/haulage capacity Grinding Index (Bond Index) for crushing and grinding Manpower productivity (= f(mechanisation) Equipment types for energy consumption 17

18 Main inputs for OPEX (O Hara Model ) Man power productivity Man power cost Mining method Processing method Indirect and general costs (structure of the company) 18

19 MAFMINE A group of researchers from the Federal University of Rio Grande do Sul is developing a software. Called MAFMINE Based on MAFMO and the O'Hara formulations with adjustments made to capture modern mining technology costs.

20 MAFMINE - academic purpose software Tool to support pre-scooping studies, due diligences and operational bench marking. Deliverables: CAPEX estimation, OPEX, workforce and infrastructure needs. Involved the use of a computer model known as client-server. 20

21 Investment Operating Cost Some features present in MAFMINE software Export of Data for Risk Analysis (in the implementation phase) Save project settings Change of base year and country estimates Print report data Model Customization for different users (in the implementation phase)

22 Cloud computing

23 Cloud computing

24 Platform

25 Architecture of MAFMINE

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28 RESULTS AND DISCUSSION Some results obtained with MAFMINE software.

29 Results are compared in two distinct situations CASE 1 - the conceptual study of an open pit copper mine (performed by a consulting firm) is tested by comparing the CAPEX between the consultant and MAFMINE. CASE 2 - compares the OPEX from MAFMINE to the result obtained by applying Stebbins methodology (SHERPA) and the actual OPEX from an underground coal mine. Cases 1 and 2 are focused on operations in Brazil.

30 Daily ore production: t Daily waste production: t CASE 1 Open pit copper mine Initial stripping: Mt (80% without explosives and 20% use explosives) Ground conditions of beneficiation plant: flat with less than 3m of earthmoving Ground support of building foundations: resistant soil with low humidity Climatic characteristics: tropical Processing plant capacity: t / day Work Index = 16 Electricity: high voltage provided by the existing system located 50 km away

31 Values proposed by case 1 investment consulting firm (Carriconde, 2010)

32 Report generated by MAFMINE Case 1 open pit copper mine

33 Result Case 1 CAPEX (Consultant project) US$ 180,5 million CAPEX (MAFMINE) - US$ 200 million The overall results are very similar to obtained by the conceptual study. The total value of investments made by MAFMINE exceeds the conceptual study by 10.85%. Some individual values present a bit more difference, such as prestripping and mining equipment. These are items that should be investigated in the model.

34 CASE 2 Coal mine underground mine Year 2013 Underground Coal Mine Method- Room and Pillar Country Brazil/Santa Catarina State/ Criciúma City

35 CASE 2 - Value comparison Stebbins, MAFMINE, Actual Mining Method Project Production ROM (t/year) Actual OPEX (US$/t; 2013) STEBBINS (US$/t; 2011) MAFMINE (US$/t; 2012) Room and Pillar Underground Coal/Criciuma ,74 20,18 19,8

36 Conclusion Mining cost evaluation Reliability is proportional to the quality of information available from the ore body. Reliability also increases with the level of effort involved in finding and evaluating information. Cost estimation constitutes an interactive process. The more information is available for reviews, the greater the reliability of the estimated costs.

37 Conclusion "Quick Evaluations" are less accurate but easier and applied faster than a conventional design. Results can be evaluated and adjusted on each compilation documenting all assumptions and the data source. Require little information but when combined with experience can provide good results. It should be noted that results with reliability can only be achieved with a good understanding of the deposit and diligent work.

38 Thank You!!!