Modifying and Updating the Underground Mines’ Cost Estimator Based on World and Iran Economic Conditions (Verification: in Emarat Shahin Lead and Zinc Mine)

Document Type : Research Article

Authors

1 Dept. of Petroleum, Mining and Material Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran

2 Dept. of Mining Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

10.29252/anm.2020.13697.1437

Abstract

Summary
Estimating the costs of mining projects is among the most important and main stages in justifying the economic plan of a mine. Suboleski presented a model for underground mines, which was published in the SME, Mining Engineering Handbook in 1992. It was based on the financial conditions of that time. The given relations of this model cannot be used to estimate the costs in Iran. In this study, the relations are modified and updated to present an estimation suitable with the local conditions of Iran using official statistics and data and taking the special status of Iran into account.
 
Introduction
In mine planning procedure, a pre-feasibility study has a significant role. In the pre-feasibility study, the mine planner has to achieve a plan with an accuracy of 25% while he has not enough data, hence he will be dependent on estimators. Suboleski presented a cost estimator based on annual production capacity in underground mines and the size of the mine in order to estimate machinery and costs. The given relations of this model cannot be used to estimate the underground mining costs in Iran. In this study, the relations are modified and updated to present an estimation suitable for the local conditions of Iran.
 
Methodology and Approaches
In order to modify and update the procedure, the percentage of each of the effective scopes of work in each of the relations with the influential coefficients were obtained, then the effect of the changes in currency value and the inflation status from the base year to the target year is considered in order to modify and update each of the relations. The base year in this study was 1988 because the Suboleski model which has been published in 1992, economically was based on the time value of the money in 1988 and the target year was 2019 that is the most recent year in which its financial data are available. The calculated Effective Inflation Index (EII) containing CPI, ECI, NII, PPI, GDP, and GNP was used to update the procedure.
 
Results and Conclusions
Finally a table of Suboleski’s relations due to the ratio of 2.39 to update the US dollar-time relationship and another table for the specific relations of Iran concerning the adjustment coefficients of each sector were presented (for each separate section due to the specific modification of that section calculations are provided with). Using tables and daily mined Tonnage, the users can get estimation with at least 25% precision of operating cost and capital cost of the mine in Iran. A verification took place using Emarat lead and zinc underground mine actual costs data. In every case in the verification process, the accuracy was around 20%.

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Full Text

توجه به معدنکاری زیرزمینی در جهان به سبب ملاحظات زیست‌محیطی رو به افزایش است. با توجه به روند رو به رشد تولید معادن زیرزمینی، محاسبه هزینه برای این معادن اهمیت فوق‌العاده‌ای یافته است. برآورد هزینه مهمترین بخش کار تیم مهندسی است که قبل از آغاز پروژه باید مقدار بودجه مورد نظر را با تقریبی مطلوب محاسبه نمایند. بدین منظور، روش‌های مختلفی برای پیش‌بینی سود و زیان پروژه‌ها وجود دارند. از جمله این روش‌ها، استفاده از هزینه واقعی پروژه مشابه که در برخی موارد همراه با به‌روز‌ در آوردن این هزینه‌ها است، یا روش تفصیلی محاسبه هزینه و مدل‌های آماری برآورد هزینه هستند. از جمله این مدل‌ها مدل نِیل و جِنتری[i]، مدل موسسه معدن و متالورژی استرالیا[ii]، مدل مولار[iii]، مدل دفتر معادن ایالات متحده[iv]، مدل مرکز کانادایی فناوری معدنی و انرژی[v]، مدل اوهارا و سوبولسکی[vi] را می‌توان نام برد [1-5]. این مدل‌ها پاسخگوی تخمین کامل و دقیق تجهیزات معدنی نیستند. بسیاری از آن‌ها جامع نبوده و یا از دقت کافی و لازم برخوردار نیستند [6]. اما این مدل‌ها به مهندسان در تخمین هزینه‌ بخش‌های مختلف معادن زیرزمینی کمک می‌کنند. در میان این مدل‌ها، مدل سوبولسکی جزء یکی از روش‌های قابل قبول در جهان است. علت این امر تعداد داده‌های اولیه برای به دست آوردن تخمینگر سوبولسکی است[7]. هرچه تعداد داده‌ها در مدل آماری بیشتر باشد تخمینگر از پذیرش بالاتری برخوردار است . از طرفی مدل مذکور برای گذشته بوده و نیاز است تا به‌روز‌رسانی گردد. لذا این مدل با توجه به ضرورت و کاربرد، در مقاله حاضر برای سال 2019 به‌روز‌رسانی شده است. همچنین تمامی ‌روابط برای شرایط خاص ایران نیز تغییر داده‌ شده‌اند. با توجه به اینکه واحد پول مورد محاسبه این روابط دلار آمریکا است، نوسان‌های اخیر در نرخ برابری ریال ایران در برابر دلار امریکا به هیچ وجه از دقت این روابط نخواهد کاست. مدل مذکور شامل: هزینه پاکسازی سایت، هزینه سرمایه‌ای حفر چاه دسترسی [شفت]، هزینه بالابر محصور، هزینه سرمایه‌ای سر چاه یا دکل حفاری، هزینه آماده‌سازی و تجهیز کارگاه استخراج، هزینه حفاری، بارگیری و حمل، هزینه سیستم تهویه معدن، هزینه سیستم آبکشی، هزینه سیستم آبرسانی، هزینه سنگ‌شکن اولیه نصب شده در زیر‌زمین، هزینه تعمیرگاه معدن زیر‌زمینی، هزینه سیستم کمپرسور، هزینه توزیع آب و هوای فشرده، هزینه سیستم پرکردن کارگاه کند و‌ آکند، هزینه توزیع برق زیر‌زمینی، هزینه عملیاتی معدن زیر‌زمینی، هزینه آماده‌سازی کارگاه، و سایر هزینه‌ها مانند بالاسری و سنگ‌شکنی هستند. مدل سوبولسکی مربوط به سال 1988 است و برای محاسبه هزینه حال حاضر نیاز است تا این فرمول‌ها به‌روز‌رسانی گردند[8, 9].


[i] Neil & Gentry

[ii]AusIMM(Australasian Institute of Mining and Metallurgy)

[iii] Mular

[iv] US.B.M.(United States Bureau of Mines)

[v] CANMENT (Canada Center for Mineral and Energy Technology)

[vi] O’Hara & Subolski

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Journal of Analytical and Numerical Methods in Mining Engineering
Volume 10, Issue 24
November 2020
Pages 1-12

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History

  • Receive Date: 04 January 2020
  • Revise Date: 20 May 2020
  • Accept Date: 04 July 2020

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