Learning and Discussion of Innovative ideas about Mining Waste Management and also Mining Related News and Activities

  • Mine Waste Management Training

    Mine Waste Management Short training sponsored by Government of Japan through JICA in corporation with the Government of PNG through CEPA, MRA and DMPGM.

  • Mount Sinivit Mine

    Acid mine drainage (AMD) continues to flow from the abondoned workings (mine). It is of two types and they are Mine Drainage from underground and open-pit and the seepage water from waste dump and tailings dam.

  • Mining Warden Hearing at Ok Isai Village, Frieda River, East Sepik Province, PNG

    Landowner grievances is always a challenge for the PNG Mining Industry. However, the Regulators of the Mining Inductry facilitate Mining Warden Hearings and Development Forums to address grievances related to mining.

  • Osarizawa Underground Mine Adit

    Osarizawa Underground Mine is an abandoned mine in Akita Prefecture, Japan. Event though the mine is closed, the mine site is kept for sightseeing purposes.

  • Hidden Valley Tailings Storage Facility (TSF)

    Mine Waste refers to the waste related to mining activities such as tailings and waste rock. Management refer to how the mine derived waste is managed by the operator and or the Regulatory Body.




Showing posts with label Mining Engineering. Show all posts
Showing posts with label Mining Engineering. Show all posts

Tuesday, 31 July 2018

Discounted Cash Flow Modeling(Simple) - Mineral Economics


PRODUCTION

·         30,000 tons copper per day for 350 days for 20 years
·         Through put recovery is 87 % for every 1 tonne mined.
·         Cu ore grade is 0.8 % tone Cu per mill tonnage produced
·         Price of Cu is projected to be US$ 1.25/lb

Now: 30,000 x 350 = 10 500 000 tonnes/year of Copper  ore
For 20 years = 10500000

Now: 87% through put recovery for every 1 tonne mined:
0.87 x 10 500 000 tonnes = 9 135 000 tonnes recovery from through put per year

0.8% tones copper per mill tonnage produced (is the Cu grade)
0.008 % x 9 135 000 = 73 080 tonnes of Cu recovered per year

Now conversion of 1.25/lb to price/tonnage
2204.62 lb = 1 tonne
1 b = x
2204.62 x = 1
x = 1/2204.62 = 4.536x10 -4

Price of Cu =  US $ 1.25/4.536x10 -4  tonnes
Now :  1.25 = 4.536x10 -4
x = 1
1.25 = x 4.536x10 -4
x = 1.25 / 4.536x10 -4
= 2, 733.775

Price of Cu = US$ = 2,755.775/tonnage
Therefore the value is:
73080 x 2755.77 = US$ 201, 392, 037.00

CAPITAL COST

Real escalation = 4/Inflation in 2010 = CPI Dec. 2010     – 1      = 219.2   -1    = 0.6832 =    68.32 %
                                                                      CPI Dec. 1990                  133.8
Nominal escalation
(1+0.6832) (1+0.04)20 - 1
= 2.589 = 258.9 %

Cost (Capital Cost 2010) = 600 M x (1+2.589) = 2 153 400 000
Working Capital 2010 = 70 M x (3.589) = 251 230 000
Salvage Value = 2 153 400 000 x 20% = 430 680 000
Now: 60% of Capital Cost is Debt = 1 292 040 000
(Debt Life = 10 years)
A = 0.12 (1 +0.12)10 x 1 292 040 000 = 228 670 619.5 (annual repayment
       (0.12 +1)10 - 1
Equity: 2 153 400 000 – 1 292 400 000 = 861 360 000
So now: 1 292 040 000/ 10 yrs = 129 204 000 (principal)
228 670 619.5 – 129 204 000 = 99 466619.5 (interest expense)
Total Capital COST = 2 153 400 000
Equity = 861 360 000
Working Capital = 251 230 000
Salvage Value = 430 680 000
Interest Expense = 99 466 619.5
Principal (Repayment) = 129 204 000
                                                                                           

OPERATION COST

Cost Projected From two cost parameters
Ø  Mining Operations Cost Involving disposal of waste and ore extraction and handling
Ø  Mining, Severance and Adminstration Operation Cost

1.      Total Ore and Waste tonnage is 90000 tonnes mined/day for 350 days and its costs $1 /tone to remove both waste and ore.
Calculate 1990 values and convert to 2010 value

Now: Nominal escalation ( OF 20 years from 1990 -2010) = 258.9% 
Cost (1990) For mining $1 /tone x (1+ 2.589) = 3.5.89/tone (2010 value)
Mining Cost = 90, 000 x 350 x 3.589 = 113 053 500 (2010 value)
2.      Milling, severance and administration
Milling Cost for 2010 = 1.6 x 3.589 = 5.7424 /tone
Severance cost 2010 = 0.1 x 3.589 = 0.3589 /tone
Administration Cost in 2010 = 0.2 x 3.589 = 0.7178 /tone

Therefore the total is give as:  6.8191
Now: 6.8191/ 0.87 = 7.838
NOW: 7.838 x 30 000 x 350 = 82 299 482.76 (milling cost)
Total operation cost = 113053500 + 82 299 482. 76
= US$195, 352, 982.80 per year


ECONOMIC FUNCTIONS

Ø  Royalty is 2% plus MRA levy of 0.25 % from year 2 to 12  and next 10 years PNG Government intends to remove MRA levy starting year 13 at the production years.
Ø  Income Tax Rate = 30% of the corporate income
Ø  In high production periods, year 2 – 14, apply double Declining Balancing method (1/2 year convention) and then switch to straight line depreciation starting year 15 to mine closure in year 22.
Ø  Real escalation = 14 years
Ø  Risk free rate of return = 4 %
Ø  Beta = 1.0%
Ø  Global Mining Industry rate of return is 6%
NB: The initial inflation is applied in year 2 to year 12 will increase by 2.5% from year 13 to 22
Now: the expected rate of return on stock investment
ECRi = Rf + I [Rm –Rf]
         = 5% + 1% (6%-5%)
         = 6%
Weight Average cost of capital
=WACC = E (Ri) x D/(D+E) + D/(D+E)X (1-t)X i
=6% x 60/(60+40) + 60/(60+40)x (1-0.3)x 12%
=8.64% (nominal Discount Rate)
Inflation 2010 = CPI (Dec.2010)   -  = 219.2  -1  = 0.6382 = 63.82%
                              CPI (Dec. 1990)       133.8
 

Average Inflation =   219.2     1/20     - 1 = 0.024989 = 0.025
                                     133.8
Therefore the inflation rate to be used is:  2.5 %


Summary of the Discounted Cash Flow Model

Discounted Cash Flow (DCF) analysis provides useful techniques to assess in terms of value maximization and cost minimization which addresses financial efficiency objectives.

The DCF analysis is a techno – economic technique applied to convert Profit Lost statement to evaluate financial viability of a new project/investment options. The criterion for decision making are not limited to NPV,IRR/ROR,DPP & KE but must also consider other risk such as environment impacts, political and socio – cultural conditions.

Gross revenue increases over the period beginning at year 2 to 22 as seen from our calculation.

Depreciation during Double Declining Balance Method of depreciation, it decreased slowly over the period from year 2 to year 14. In year 15 to year 22, straight-line depreciation method is used and so the depreciation value is constant. During the exploration stage, in year 0 to 1, there was only cash out-flowing only but from year two and upwards, there is cash in-flow.

It is seen from our results that, the NPV is $ 8,058,113,286.68. So the project is viable because NPV is greater than zero (>0). The IRR is 56.29% which exceeded the discount rate, as such it gives and impression that Frieda Copper Project is viable.
Capital Efficiency (KE) is a measure of project profitability on the capital invested. It must be greater than zero (>0) to meet the condition to be viable. Since our calculated KE is 3.74 > 0, it is better.

Scenario analysis applies DCF model variables to investigate likely scenarios if changes occur in the future. These scenarios could be increase or decrease in these variables with respect to DCF model. It is seen from the Scenario Analysis Spider Chart and we conclude that NPV is more sensitive to both positive and negative changes in revenue or price. Therefore if there is a positive increase in price, the NPV improves proportionally and vice versa if decreases

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Sunday, 29 July 2018

Mining Equipment Supplier Selection - Mine Management Questions and Answers Series (7)


Morobe Mining  Joint Venture (MMJV) is developing the Hiddem Valley mine and the mine is considering several supplieirs of machinery and equipment and continual service at the mine site. From experience and data available, the premier suppliers are Caterpillar, UWM Machinery and Hasting Deering. The manager identified the criterion for selecting the best service providers are based on cost, product quality, productivity and life/durability. The manager developes the following pairwise comparison matrices for each of the three four criteria.
X = CAT,Y= UWM,Z=Hastings Deering.

Cost
P/Quality
Productivity
Life/Durability
X
Y
Z

X
Y
Z

X
Y
Z

X
Y
Z
X
1
2
5
X
1
0.25
0.2
X
1
5
4
X
1
0.143
0.2
Y
0.5
1
7
Y
4
1
0.125
Y
0.2
1
3
Y
7
1
0.125
Z
0.2
0.1429
1
Z
5
8
1
Z
0.25
0.333
1
Z
5
8
1

From the above table, the cost matrix shows thatsupplier  X is “ equally to strongly preferred ” to supplier Z, but supplier Z is “equally to very strongly perferred” to supplier Y. Diagonally, it is equally preferred as it has the value of 1 which indicates one supplier is compared to itself.

The suppliers are prioritised within each criterion. For example, the manager intend to know which is the most preferred supplier, the second, third  within each of the four criteria. Mathematically, it is complex but it only employ approximation method to estimate preference scores. The first step is to sum the values in each column of pairwise comparison matrix as shown below for cost matrix(a).

Step  1
(a)


(b)





Cost  
Cost
Supplier
X
Y
Z
Supplier
X
Y
Z

Row Average
X
1
2
5
X
0.588
0.6364
0.3846
0.5364
Y
0.5
1
7
Y
0.294
0.3182
0.5385
0.3836
Z
0.2
0.1429
1
Z
0.118
0.0455
0.0769

0.08
Sum
1.7
3.143
13
Sum
1

In (a) the cost synthesization is done by adding cost pairwise comparision rating matrix. In (b) each column of cost pairwise comparison rating matrix is divided by the corresponding column sums (i.e. 0.5/1.7 = 0.294). it is also notice that at (b), each column sums to 1. Next, the values in each row are averaged as shown on the right hand side of the table above. Also column sum is 1 for the average values.

Step 2. Compare qualities.

The procedures applied above in cost comparison matrix is applied to the other comparison criterion and only the results (row averages) are tabulated for each supplier as given below. The row averages provide the company with its prefernces for each criterion. For examlpe, for the cost criterion, supplier  X is most preferred followed by supplier Y and supplier Z.


Supplier
Cost
P/Quality
Productivity
Life/Durability
X
0.5364
0.0927
0.6597
0.0812
Y
0.3836
0.2008
0.2236
0.2474
Z
0.08
0.7065
0.1167
0.6714
Sum
1
1
1
1

The prioritized decision criteria according to pairwise comparisions are shown below. Note that the corresponding columns are summed.

Criteria
Cost
P/Quality
Productivity
Life/Durability
Cost
1
0.1667
0.25
0.125
p/Quality
6
1
0.1429
0.1111
Productivity
4
7
1
6
Life/Durability
8
9
0.1667
1
Sum
19
17.167
1.5595
7.2361

 The column values of the above table have been divided by the column sums correspondingly and then averaged the rows as shown below.
Criteria
Cost
P/Quality
Productivity
Life/Durability
Row Average
Cost
0.05263
0.0097
0.1603
0.0173
0.05998
P /Quality
0.31579
0.0583
0.0916
0.0154
0.12025
Productivity
0.21053
0.4078
0.6412
0.8292
0.52217
Life/Durability
0.42105
0.5243
0.1069
0.1382
0.2976
Sum




1

The prefereence vector for the criteria consists of the row averages.

Criteria
Cost
0.05998
P /Quality
0.12025
Productivity
0.52217
Life/Durability
0.2976

It can be clearly seen that the productivity of machines is the most important criterion with its life/durability the second in decision making. The overall score for each supplier is obtained by multiplying the matrix summarising MMJV’s preference for each supplier criterion which was developed previously by the preference vector for the four criteria above. This is illustrated  in the table below.

Criteria
Supplier
Cost
P/Quality
Productivity
Life /Durability
Criteria
X
0.5364
0.0927
0.6597
0.0812
Cost
0.05998
Y
0.38359
0.2008
0.2236
0.2474
x
P/Quality
0.12025
Z
0.08001
0.7065
0.1167
0.6714
Productivity
0.52217






Life/Durability
0.2976

Below are the scores each supplier was rated.
Supplier
Score

Order  of score
X- CAT
0.411952
X- CAT
0.412
Y-UWM
0.237541
Y-UWM
0.3505
Z-Hasting Deering
0.350507
Z-Hasting Deering
0.2375

By seeing the scores above, CAT is the most preferred supplier of machineries for MMJV. MMJV must be confidence in the judgements made in pairwise comparisons if MMJV will rely on the result above. But even if the company doesn’t make its selection based on the analytical hierarchy process (AHP) result, following this process results in identifying appropriate and reliable supplier to meet company’s production needs. Hence, AHP can help identify and prioritse the criteria, and examine strenghts and weaknesses of different suppliers.

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Osarizawa Underground Mine Adit Osarizawa mine is an abandoned mine in Akita Prefecture, Japan . Event though the mine is closed, the ...

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