Excavator Selection

Gregory B S, 2002. 12th International Symposium on Mine Planning and Equipment Selection. Kalgoorlie.

Excavator Selection By B S Gr ego r y 1

Abstract The excavator selection process is quite complex due to the large number of influencing factors, many of these are variable and difficult to accurately define. The majority of mining companies prepare a tender of general specifications and suppliers will then match a product to those specifications. The mining company will then evaluate the tenders on the basis of the best available deal. In this paper, the importance of open pit excavator selection in terms of its impact on operating co sts is analysed and discussed. A rigorous process for selection is then outlined.

The Author’s Relevant Experience The author has been personally involved in excavator selection analyses resulting in purchases for the following operations: •

Bougainville Copper Limited, Panguna;

•

Murrin Murrin;

•

Cadia;

•

Telfer.

He has also been involved in numerous other analyses involving truck selection considerations including the following operations: •

Tarmoola;

•

Mt Keith;

•

Harmony.

Introduction In this paper the importance of the open pit excavator selection process is examined and a suggested methodology is outlined. The term "excavator" is used here as a collective term covering face shovels and backhoes. (The author is aware aware that the term "excavator" is sometimes used as an alternative to "backhoe".) A general observation is that there is no accepted industry standard methodology for the selection of the most suitable excavator for an open pit. As is discussed in this paper, excavator selection can have a significant impact on the efficiency and profitability of a mining operation and hence a comprehensive systematic approach is warranted. This paper primarily focuses on the selection of face shovels and backhoes for medium to large scale, hard rock open pit mining. Other types of loading equipment such as front front end

1. Principal Mining Engineer, Engineer, AMC Consultants Pty Ltd, 9 Havelock Street, West Perth, WA. Email: [email protected] [email protected]

loaders, draglines, bucket wheel excavators, scrapers and continuous miners may be valid alternatives in specific applications but these will not be discussed in detail. The selection of the type, size and operating mode of a loading unit can be a complex task governed by a number of factors that may be variable and poorly defined depending upon the maturity of the mining operation. Selection of an excavator is often dependent upon factors such as: •

mine design;

•

mine production schedule;

•

geology;

•

material characteristics performance;

and

expected

•

climate and/or environment;

•

expected reliability of the excavators;

•

capital cost and operating cost;

•

required mobility of the excavator;

•

maintenance support analysis;

•

power costs vs fuel costs.

blasting

The costing analysis presented in this paper has been performed using Australian Mining Consultants Pty Ltd's (AMC's) OPMincost cost estimation model. The version utilised was based on a mine with the following attributes: •

20 year mine life;

•

maximum uphaul of 500m;

•

total movement averaging 50 Mtpa;

•

average dry density of material ~2.5 t/bcm.

OPMincost is a comprehensive, spreadsheet-based model, which has been developed over a number of years by AMC and has been utilised utilised successfully on about 20 projects. For the version used in this analysis, the following basic assumptions were used: •

owner mining;

Excavator Selection

•

owner maintenance;

•

fuel price after rebate of A$0.36;

•

interest rate of 7.5% per annum;

•

•

•

365 day, 24 hour operation with a two and one FIFO roster.

Cost inputs were based on May 2002 budget quotations from equipment suppliers. Considerable effort has been made to validate cost inputs and model outputs, including reference to recent benchmarking data and checking with various relevant industry professionals. Although the model is based on a real project, it is not appropriate or necessary to name the project.

The Importance of Excavator Selection For Operational Profitability To put this subject in context, we should examine the importance of excavator selection in terms of its impact on operational profitability. Firstly, let us look at the proportion of total mining costs, represented by the loading activity. Using OPMincost, the contributions of the various mining activities to total mining costs were analysed. Results are summarised below in Figure 1.

Figure 1 - Total Mining Cost by Activity 5%

12% Other

10%

Drill

6%

•

•

•

•

•

insufficient selectivity may result in grade, dilution and ore loss; poor matching with haul trucks results in increased haulage costs; loading inefficiency can cause downstream problems including a poor match with processing plant capacity and haulage fleet inefficiencies; poor excavator reliability can cause significant inefficiencies downstream including haulage fleet redirection, haul truck stand-down and/or production shortfalls; poor loading performance can directly impact on ore production and hence revenue; poor loading performance can result in insufficient waste stripping which may cause ore production delays and reduced revenues; sub-optimal sizing of excavators will result in opportunity costs, especially with regard to loading and hauling activities.

The effects mentioned above are discussed in more detail below and in order to examine the significance of these effects, an order-of-magnitude profit impact has been calculated based on the example project mentioned above (low grade open pit gold, 20 year mine life, 50 Mtpa total movement). Of course, the relative magnitude of these impacts will vary significantly for different operations but the intention here is simply to illustrate the importance of excavator selection.

Dilution and ore loss effects

Blast Management & Supervision 12% Load Ancillary

17%

Haul

38%

These proportions will obviously vary from operation to operation but a check on AMC's database confirmed that loading costs typically make up between 15 to 20% of total mining costs for large open pits. Based on this analysis, it appears that loading costs may not be as important as haulage costs and it could be mistakenly concluded that less effort may be warranted in selection of loading equipment. However, because of the pivotal nature of the loading activity in a mining operation, excavator performance affects the efficiency of the whole operation, including the processing plant and excavator selection often requires as much or more effort than truck selection. In addition to its impact on the cost of the loading activity, suboptimal excavator selection may impact on operational profitability via the following mechanisms:

AMC Reference Library – www.amcconsultants.com.au

Because geology and the nature of the occurrence of ore varies widely between operations, the potential for excessive dilution and ore loss, resulting from sub-optimal excavator selection, will also vary. In narrow vein deposits this can be a major issue but in disseminated orebodies excavator selectivity may be irrelevant. In operations where selectivity is an issue, the effect of ore dilution and ore loss that could result from inappropriate excavator selection will likely outweigh any mining cost effects on profitability. For example, an indicative calculation showed that if ore dilution at the example operation mentioned above increased from 10 to 20%, the loss in annual revenue would be equivalent to approximately 50% of the total annual mining cost.

Effect of poor match with haul trucks In most cases in the author's experience, excavators are firstly selected by matching excavator production characteristics with operational requirements and then haul trucks are matched to the selected excavators. So it could be argued that poor matching of trucks and excavators is usually a truck selection issue. However, instances do occur where excavators need to be matched to an existing truck fleet so the following is relevant here. To analyse and illustrate the effect on mining costs of excavator/truck matching, five different truck sizes were matched with three different excavator sizes. A particular mining scenario - mining bulk waste from a particular bench was selected and the total cost of loading and hauling (excluding ancillary, supervision and administration costs) was determined. These costs were converted to an index for comparative purposes. The results from this analysis are listed in Table 1. This table shows:

2

Excavator Selection

•

number of passes to load the truck;

•

load time (which includes truck exchange time);

•

the cost index.

It is very unlikely that mining operations would select an excavator that is more than one class away from the optimal match, so for this analysis it is assumed that the sensitivity to a shortfall in this aspect is the difference between the cost indices of two adjacent classes. The approximate average magnitude of this difference is 5%. The effect of this truck selection shortfall on total mining costs would be approximately 2.5% because load and haul accounts for roughly 50% of total mining costs as defined in this analysis.

Research by the Parker Bay Company has shown that the industry average number of passes per truck load is five. The results shown in Table 1 tend to support this. See also Figure 2 which shows a minimum cost index around four to five pass loading for the 650t and 400t excavators but an unexpected result for the 100t excavator where cost efficiencies of larger trucks override the excavator/truck match effect.

Table 1 - Analysis of the effects of excavator/truck matching on load and haul costs Excavators

Operating Weight (t) Bucket Capacity (cu.m)

100 6.5

400 20

Truck Size (Payload) (t)

Number of Passes

Load Time (min)

Cost Index (%)

49 91 146 187 230 353

4 7 12 15 18

2.13 3.48 5.73 7.08 8.43

200% 144% 130% 126% 134%

650 34

Number of Passes

Load Time (min)

Cost Index (%)

Number of Passes

Load Time (min)

Cost Index (%)

2 3 4 5 8

1.25 1.72 2.18 2.65 4.05

125% 114% 104% 101% 110%

2 3 3 4 6

1.25 1.72 1.72 2.18 3.12

135% 115% 102% 100% 106%

Figure 2 - Excavator cost index vs number of truck passes 230%

210%

190%

170% ) %150% ( x e d n I t s 130% o C

100 tonne excavator

400 tonne excavator 110%

650 tonne excavator

90%

70%

50% 1

2

3

4

5

6

7

8

9

10

11

12

Number of Truck Passes


3

Excavator Selection

Effect of loading inefficiency on hauling costs and total mining costs In this scenario inefficiencies that relate to sub-optimal matching of excavators to digging conditions is examined. Examples here include:

To quantify these potential effects, the following arbitrarily determined parameter changes were made to the OPMincost model: • •

•

•

Poor match of excavators to bench height. There is a bench height range where each size of face shovel and backhoe performs at maximum efficiency. Outside that range inefficiencies relate to problems like poor bucket fill and frequent repositioning where the bench is too low, or rilling and safety problems if the bench is too high. For reasons of selectivity and/or operational efficiency, bench (or flitch) heights cannot always be adjusted to suit the digging characteristics of the excavator. Inappropriate excavator attachment configuration resulting in insufficient breakout force and/or digging power. This situation can arise during the selection process where insufficient attention is paid to material characteristics such as expected density, fragmentation and swell factors.

To analyse this effect the digging efficiency factor within OPMincost was reduced by 10%. The result of this was: •

10% increase in loading costs

•

1% increase in hauling costs

•

2% increase in total mining costs.

Effect of poor excavator reliability on hauling costs and total mining costs Poor reliability is defined here to mean frequent breakdowns. The most common measure of this aspect is the mean time between failures (MTBF). Reliability is related to availability (the time the machine is available for productive use divided by calendar time) but reliability reflects the level of operational disruption (inefficiency) caused by breakdowns. Poor excavator reliability can be related to excavator selection if the problem is a function of the excavator design, suitability of the machine for its duties, performance of parts suppliers or technical backup of equipment suppliers. All these issues need to be thoroughly researched and responded to in the selection process.

•

•

•

Increased maintenance costs, especially through inefficient use of maintenance resources. This is because poor reliability implies frequent unplanned maintenance activities.

•

2% increase in haulage costs

•

4% increase in loading costs

•

1% increase in total mining costs.

As for the effects of reduced ore production, again the relative importance compared to other cost impacts will vary greatly from operation to operation but generally this effect is the most serious in terms of potential impact on profitability. For example, an indicative calculation showed that if annual ore production was reduced by 5% for the example operation mentioned above, the loss of revenue would be equivalent to approximately a 20% increase in annual mining costs.

Effect of excavator sizing on load and haul costs The OPMincost model was used to analyse the effect of excavator sizing on load and haul costs. It was not considered appropriate to compare loading costs in isolation. This is because of the effect that changes in loading time have on haulage costs and because haulage costs usually make up about 40% of total mining costs whereas loading costs only account for about 15 to 20% for large hard rock open pit mines. Load and haul costs for five different excavator sizes and four truck sizes were calculated on the basis of a fixed mining schedule. To simplify analysis, auxiliary equipment costs were not included in this analysis. In general, inclusion of auxiliary costs would tend to make the larger excavators look more attractive because the number of loading units and hence cleanup dozers would be lower. Load and haul costs were converted to indices relative to the lowest cost alternative and these results were plotted as shown in Figure 3. Equipment matches that were not seen as practical were not included. Conclusions that were drawn from this analysis are:

•

•

Production shortfalls caused by reduced effective excavator hours. The most serious potential consequence of this would be loss of revenue due to interruption of ore supply to the processing plant. Haulage fleet inefficiencies, especially where unexpected excavator breakdowns cause unplanned re-allocation of haulage resources.


Increase of 10 minutes per shift in trucks waiting for excavators.

These resulted in a:

•

A mining operation can be affected by poor excavator reliability in the following ways:

10% increase in excavator maintenance costs

•

Truck size is a more dominant driver of load and haul than excavator size. The lowest load and haul cost was achieved with the combination of the largest mining equipment analysed. Given a particular truck size, the largest excavator did not always result in the lowest cost index. This was due mainly to the fact that lowest costs are generally achieved where shovel bucket and truck tray capacities are well matched. For a good excavator/truck match, each swing of the excavator delivers the maximum bucket payload and load time is not excessive. As mentioned previously, usually four to six pass loading delivers the best results. Given a particular truck size, load and haul costs varied in a range of +5% with different excavator sizes.

4

Excavator Selection

Figure 3 - Load and haul cost indices 135%

125%

115% Truck Payload 91.2 t 146 t

105%

187 t 230 t

95%

85%

75% 100

180

250

500

700

Excavator Sizes (Tonnes Op. Wt.)

Summary of potential impacts on profitability The abovementioned indicative potential impacts on profitability that could be caused by excavator selection shortfalls are summarised below in Table 2.

Figure 4 - Potential impacts on profitability (in terms of percentage of total mining costs)

50%

Table 2 - Summary of potential impacts on profitability

45% 40%

Effect

Type of Impact

Potential Impact on Profitability (converted to equivalent total mining cost percentage)

Dilution due to poor selectivity

Revenue

Poor match with haul trucks

Mining cost

2.5%

Inefficient loading

Mining cost

2.0%

Revenue

20.0%

Poor excavator reliability

50.0%

35% 30% 25% 20% 15% 10% 5% 0%

Please note, the profitability effects relating to dilution and reliability were quantified in terms of loss of revenue. These quantities were converted to an equivalent total mining cost for comparison purposes. Obviously these effects are potentially very significant and their magnitude highlights the importance of excavator selection.

Dilution

Inefficiency

Description of a Rigorous Process For Loading Unit Selection Key considerations The following key considerations need to be addressed in the selection process: •

Selectivity requirements −

Refer to Figure 4 for a graphical representation of these effects. •


Poor Reliability Truck Match

geological occurrence of the ore will influence selection of the mining method and excavator size and type required to minimise dilution and ore loss effects.

Maximum production material types.

requirements

of

various

5

Excavator Selection

•

E.

Develop/customise cost estimation model.

F.

First pass analysis and maintenance cost estimation.

G.

Prepare and distribute tender requests for excavator supply.

considering capacities and loading heights.

H.

Expected digging characteristics of material to be mined

Prepare and distribute tender requests for contract maintenance.

I.

Finalise analysis.

Blending requirements −

•

Matching to haul trucks −

•

may require ore from several sources to be delivered at specified feed rates.

−

for example, loose density, fragmentation, swell factor.

•

Minimum mining width required.

•

Excavator mobility requirements −

•

•

Ideally, the following fields of expertise would be represented on the excavator selection team:

how often does the excavator need to relocate and how far does it have to move?

Electric rope shovel versus hydraulic excavator −

A - Assemble a cross-functional team

electric rope shovels are most competitive in bulk mining situations and where power costs are reasonably low.

•

Operations.

•

Maintenance.

•

Mine planning.

•

Financial analysis.

•

Contract administration.

Face shovel versus backhoe configuration −

usually driven by selectivity considerations. Face shovels require higher bench heights for efficient digging.

•

Reliability of excavator.

•

Reliability of suppliers/support.

•

Operating costs:

B - Determine key operational requirements and analyse where necessary In hard rock mining the three main operational requirements to be considered for excavator selection are production rate, selectivity and flexibility. •

−

life-cycle maintenance

−

fuel/power and lubrication

−

operator costs

−

GET.

•

Capital costs.

•

Lead time for delivery.

•

New versus second-hand equipment.

•

Residual/salvage values.

•

Cost analysis (preferably Net Present Cost).

•

Industry trends.

Production rate - to match waste stripping schedules and required ore delivery rates to the process plant. In mature operations the estimation of production rates should be fairly reliable because of experience with the diggability of materials to be mined. However, for a greenfields operation, estimation can be more difficult because of uncertainty in predicting the main productivity factors such as: −

−

Suggested process Different circumstances may require markedly different approaches to that described below. The following process is based on a situation where: •

•

•

•

Time constraints (in relation to the selection process) are not overly onerous. There are no special relationships between the purchaser and any particular supplier group. Excavators would be owned (or leased) by the mine owner.

−

swell factors which are related to material characteristics and blasting performance (fragmentation); bucket fill factors which vary according to material characteristics, blockiness, fragmentation, operator performance, bench heights etc; cycle times which can be affected by digging conditions.

In estimating these factors it is useful to have access to a database of comparable, measured examples. That is, previous performance in similar material-types may be the best starting point for estimation factors. Note that, in relation to production rates, mine planning and excavator selection can, in some situations, be an iterative process comprising variations of the following steps:

Mine life exceeds the economic life of the excavators. −

In summary, the suggested process would be: −

A.

Assemble a cross-functional team.

B.

Determine key operational requirements and analyse where necessary.

C.

Review industry trends.

D.

Request detailed suppliers.

information

from

−

a mine plan is developed to satisfy production targets; excavators are selected that best meet the mine plan requirements and satisfy other criteria, eg least cost; the mine plan may be adjusted to take advantage of any excess excavator capacity.

equipment


6

Excavator Selection

Selectivity. As discussed in the previous section, the importance of mining selectivity for operational profitability varies widely between mines according to the style of occurrence of mineralisation. Where selectivity is an issue, careful analysis is warranted because of the need to find the appropriate trade-off between dilution/ore loss and mining costs.

•

This aspect can be analysed using standard integrated mine planning software such as Datamine. The methodology for this analysis can be summarised as follows. For each excavator type and size: −

−

re-block the resource model to match the excavator's selective mining unit dimensions, producing uniform blocks with diluted grade; apply appropriate mining and processing costs to orebody model blocks;

Figure 6 - Effect of mining block size on ore grade reef deposit 102%

100%

21 cubic metre backhoe e s a c e s a b o t e v i t a l e r e d a r G e r O

26 cubic metre shovel 98%

35 cubic metre shovel 38 cubic metre rope shovel

96%

50 cubic metre rope shovel

94%

92%

90%

88% 0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000 10,000 11,000

SMU Volume (Bcm) −

apply appropriate metallurgical recoveries for calculated grade ranges;

−

apply profit algorithm;

−

calculate total operating cashflow;

−

plot results of operating cashflow versus excavator size.

An example of such a graph is shown below in Figure 5.

Figure 5 - Operating surplus versus excavator bucket size - reef deposit 110%

105%

This graph shows that with this type of deposit, the larger the block size the more dilution of ore grade. Figures 7 and 8 show the same relationships as described above (ie, cashflow versus excavator bucket size and ore grade versus mining block size) for more disseminated (actually a quartz stockwork deposit in this example) ore deposits where selectivity is less important. As can be seen in Figure 7, the economics of using larger mining equipment balance out the benefits of selectivity and, on the basis of this graph, it would be equally valid to select a 21m3 backhoe or a 50m3 rope shovel. Clearly other operational factors should be considered in conjunction with this analysis in order to make the appropriate selection.

21 cubic metre backhoe 26 cubic metre shovel

e 100% s a c e s a b 95% o t e v i t a l 90% e r w o l f h s 85% a C

•

35 cubic metre shovel 38 cubic metre rope shovel 50 cubic metre rope shovel

80%

75%

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

SMU Volume (Bcm)

Please note that the shape of the curves will vary from operation to operation in accordance with geological, operational and cost variations. Also, the curves on the graph have resulted from analysis of a reef type deposit where selectivity is a significant factor. The average diluted ore grade resulting from selective digging with the smaller excavator, is higher than for the larger excavators. In this case the 21m3 backhoe should be selected because it would provide the best operating surplus. Figure 6 shows an example of the effect of mining block size on diluted ore grade in a reef type deposit where selective mining is desirable.


Flexibility. In this context, flexibility relates to the ability of an excavator to respond to changes in digging requirements. These requirements may involve selectivity issues and/or the need to relocate the excavator between different material types or mining areas on a regular basis.

In terms of selectivity, backhoes are more flexible than face shovels and hydraulic faced shovels are more flexible than electric rope shovels, due to the digging actions of the machines. Backhoes can better selectively mine flat-dipping deposits than face shovels and backhoes can also selectively mine to steeply dipping contacts. Face shovels can usually mine selectively to steep dipping contacts. Rope shovels have a fairly restrictive digging action because the bucket must mainly be lifted vertically through the face so selective mining is usually not suited to these machines. In terms of flexibility to relocate, hydraulic excavators are more mobile than electric rope shovels because they typically travel at about 2 kph compared to 1 kph for rope shovels. Also, the cable-handling work required when relocating rope shovels necessitates the use of more resources. To better balance the comparison between electric rope shovels and hydraulic excavators it should be noted that rope shovels remain the loading tool of choice for a significant proportion of applications worldwide. These machines are especially suited for bulk mining applications where frequent shovel-moves are not required and where power costs are attractive.

7

Excavator Selection

Figure 7 - Operating surplus versus excavator bucket size - quartz stockwork deposit

D - Request detailed information from equipment suppliers This request would generally include the following:

110%

105% e s a C e 100% s a B o t e 95% v i t a l e r

•

Reason for request.

•

Description of operation including: − −

w o 90% l f h s a C g 85% n i t a r e p O 80%

35 cubic metre shovel 38 cubic metre rope shovel 50 cubic metre rope shovel

75% 0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

−

mining rate;

−

estimated number of excavators required.

Budget pricing.

•

Component replacement schedule and parts pricing.

•

Maintenance labour hours estimate component replacement schedule.

to

•

Average fuel consumption rates.

•

Lubrication consumption rates.

•

Technical specification.

•

Maximum suspended load and bucket weight.

102% •

100%

e s a c e s a b o t e v i t a l e r e d a r G e r O

mine life;

•

SMU Volume (Bcm)

Figure 8 - Effect of mining block size on ore grade quartz stockwork deposit

material characteristics such as density, swell factors etc;

−

21 cubic metre backhoe 26 cubic metre shovel

description of loading duties;

•

match

A listing of equipment numbers in the state, country and worldwide. Estimated delivery time from time of order.

98%

E - Develop/customise cost estimation model

96%

This model needs to cover all costs that would be affected by the excavator selection decision so that the total cost of alternatives can be compared. It is usual practice that Net Present Costs (NPC's) are calculated and compared so that the time value of money is taken into account.

21 cubic metre backhoe

94%

26 cubic metre shovel 35 cubic metre shovel

92%

38 cubic metre rope shovel 90%

50 cubic metre rope shovel

88% 0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000 10,000 11,000

SMU Volume (Bcm)

C - Review industry trends It is useful to understand trends within the industry because these will reflect the opportunities that are available currently and in the future as a result of excavator selection. For example: •

• •

•

•

•

Is the trend towards electric rope shovels or hydraulic excavators? Why? What is the most popular excavator size? What cost-cutting implemented?

developments

are

being

What new technological developments are likely to be available in the near future? Is owner-maintenance becoming more popular?

or

OEM

maintenance

Which makes and models of excavators are selling the most and how happy are current users?

Methods of review are many and varied, including literature search, suppliers' information, field visits, conferences, internet searches, magazines, utilising specialist consultants and visiting manufacturing plants.


Development of comprehensive cost estimation models can be a time-consuming process. AMC's approach is to minimise this time by customising the OPMincost model for each application. A flow diagram representing OPMincost methodology is presented in Figure 9. In brief terms OPMincost calculates equipment productivities and hourly operating costs and combining the two calculates the total cost of the respective activity such as load and haul. Inputs to the cost estimation model, eg OPMincost include: •

Truck travel times and average fuel consumptions for each haul profile.

•

Mining schedule.

•

Truck specifications.

•

Excavator specifications.

•

Equipment maintenance costs.

•

Calendar and operating roster parameters.

•

Material characteristics.

•

Equipment operating cost parameters.

•

Wage rates.

•

Operating delay estimates and efficiency factors, etc.

Outputs required from the cost estimation model to compare alternatives include:

8

Excavator Selection

•

•

Excavator productivities and numbers required to meet the mining schedule. Number of trucks required to meet the mining schedule.

•

Total load and haul operating costs.

•

Total load and haul ownership costs.

•

Total load and haul cash flows.

•

Load and haul NPC.

It is also preferable to produce the following outputs to provide a clear understanding of equipment combination scenarios and allow for reality checks, eg comparing with statistics from other operations: •

Total annual operating hours.

•

Total operating personnel requirements.

•

Total maintenance personnel requirements.

•

Hourly maintenance costs.

Figure 9 - OPMincost flow diagram - load and haul costing version

Determine Haul Profiles

Set Basic Inputs

Talpac Analysis

Talpac Inputs

Costing Parameters Productivity Parameters Material Characteristics

Truck Travel Times and Fuel Consumptions

Calendar Parameters

Calculate Excavator Productivities

Excavator Productivity Load Time Payload

Calculate Truck Productivities and Match to Excavators

Truck and Excavator Productivities

Calculate Equipment Hourly Costs

Available Equipment and Labour Hours

Calculate Truck and Excavator Hours

Annual Equipment Hours

Annual Labour Hours

Operating Hours

Caculate Maintenance Labour Numbers

Calculate Operator Numbers

Calculate Truck and Excavator Costs

Mining Schedule Quantities

Calculate Wages Costs

Misc. Fixed Costs

Calculate Excavator and Truck Numbers

Calculate Ownership Costs

Calculate Load and Haul NPC

F - First pass analysis and maintenance cost estimation

gaining an understanding of issues and opportunities and developing a tender request short-list.

Carry out a first pass analysis using the cost estimation model and discuss options with equipment suppliers, with a view to AMC Reference Library – www.amcconsultants.com.au

9

Excavator Selection

It is during this phase of the analysis that maintenance cost projections are developed. This is a very important exercise (maintenance costs account for approximately 50% of loading costs), especially if owner-maintenance is being considered but even if contract maintenance is preferred, results provide a useful check on tendered contract maintenance rates. A checklist for items to be included in maintenance costs follows:

new fleets of mining equipment are acquired. Possible reasons for this are: •

•

The risk of maintenance costs being underestimated is reduced. The problems associated with the owner recruiting and managing the maintenance crew is largely eliminated.

•

Freight.

•

Lubrication fluids.

•

On-site and/or off-site labour costs.

•

Unscheduled maintenance allowances.

•

Bucket maintenance.

I - Finalise analysis

•

Supervision and management.

The steps involved here include:

•

Tooling.

•

GET replacement costs.

•

Cranage.

• •

Servicing costs.

•

Outcomes from contract maintenance from the owner's perspective have been quite good in terms of maintenance costs and equipment availability.

•

Review of tender responses.

•

Discussion and negotiation with tenderers.

•

Oil sampling.

Projected from time to time, these items may either be included or excluded from suppliers life-cycle maintenance cost projections. •

•

•

• •

Validation of key aspects of tender responses by checking actual industry experience. Calculate NPCs using the cost estimation model, incorporating tender responses. Carry out a risk analysis. If necessary, prepare a decision matrix to assist in finalising the selection.

Major component lives should be checked against experience from other operations and from truck to truck to improve confidence in the numbers.

Conclusion

It is preferable to have projections checked by an experienced haul truck maintenance professional.

The main messages to be noted when planning an excavator programme are that:

G - Prepare and distribute tender requests for excavator supply Prepare and distribute requests for tenders for the supply of excavators.

H - Prepare and distribute tender requests for contract maintenance

•

•

•

The potential operating cost and production revenue impacts of excavator selection shortfalls are significant. A rigorous process should be followed in an effort to make the best possible selection. Thorough research needs to be carried out to determine the status of the market, industry trends and to validate suppliers' information.

Prepare and distribute requests for tenders for the provision of contact maintenance services, if required. In open pit mining there is currently a definite trend in the industry towards contract maintenance in preference to owner-maintenance when


10

Excavator Selection

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