Selecting Shaft or Decline

McCarthy P L, 1999. Driving Down Haulage Costs, Kalgoorlie, Western Australia

Selection of Shaft Hoisting or Decline Trucking for Underground Mines

By P L McCarthy

Introduction

• The progression from open pit mining to underground mining via a decline to shaft hoisting can be logically determined. • The economic transition from decline haulage to shaft haulage depends on several factors, particularly the production rate

and depth of mining. • Advances in trucking technology in recent years has extended the depth of changeover from truck haulage to shaft haulage.

Future advancements in trucking technology will challenge the current changeover limits. • This presentation discusses the economic and practical parameters which determine the transition from decline to shaft

haulage in underground mines. ____________________ 1. MAusIMM, CPMin, Managing Director, Australian Mining

Consultants Pty Ltd, 19/114 William Street, Melbourne Vic 3000. E-mail: [email protected]

Ore handling; decline haulage verses shaft hoisting

Reclaim Loader

Surface ProcessingPlant

Surface Stockpile

Truck

Load Haul Dump Unit

Surface ProcessingPlant

Conveyor

Headframe Bin

Skip

Loading Station

Conveyor

Crushed OreStorage

Primary Crusher

Ore Pass

Truck

Load Haul Dump Unit

BROKEN OREFrom Stope/draw point Shaft HoistingDecline Haulage


AMC Reference Library – www.ausmin.com.au

2

Northcote and Barnes 1973

• Decline haulage with 35-40t trucks. • Truck speed 7kph uphill on an average 1 in 10 grade. • Mine production less than 1 mtpa. • 12% discount rate. • Trucking depth limit 350m if sufficient ore below 350m to amortise shaft over 15 years.

Comparison of the Economics of Truck Haulage and Shaft Hoisting of Ore from Mining Operations by GG Northcote and ELS Barnes in The AusIMM Sydney Branch Transportation Symposium October 1973 McCarthy and Livingstone 1993

• Decline haulage with 40-50t trucks (Toro 40D and Elphinstone 73B). • Gradients 1 in 7, 1 in 8, 1 in 9 considered. • Mine production rates 0.25 to 1.5 Mtpa. • 10% discount rate. • Shaft never economically justified within range considered. • Depth and tonnage limits set by truck performance and ventilation.

Shaft or Decline? An Economic Comparison by PL McCarthy and R Livingstone in Open Pit to Underground: Making the Transition AIG Bulletin 14, 1993 pp45-56

Additional cost of hoisting shaft (1993 results)

DYNAMIC MODEL RESULTSCOST PENALTY FOR RAISEBORED SHAFT

0.0

5.0

10.0

15.0

20.0

25.0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

YEAR OF COMMISSIONING SHAFT

AD

DIT

ION

AL

DIS

CO

UN

TED

TO

TAL

CO

ST

($M

) 250,000 TPA500,000 TPA750,000 TPA



3

Additional cost of bored hoisting shaft (1993 results)

DYNAMIC MODEL RESULTSCOST PENALTY FOR CONVENTIONALLY SUNK SHAFT

0.0

5.0

10.0

15.0

20.0

25.0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

YEAR OF COMMISSIONING SHAFT

AD

DIT

ION

AL

DIS

CO

UN

TED

TO

TAL

CO

ST

($M

)

250,000 TPA500,000 TPA750,000 TPA1,000,000 TPA1,250,000 TPA

Moser 1997

• Survey of about 50 mines. • Former open pits developed as declines to 600m depth and 600,000tpa. • New mines less than 300m depth and less than 400,000tpa then decline only. • New mines more than 400,000tpa or more than 300m deep have a hoisting shaft.

Shaft Versus Ramps - An Empirical Decision Model by P Moser in SME Annual Meeting Denver Colorado February 1997 Cannington Study

0000

200200200200

400400400400

600600600600

800800800800

1000100010001000

1200120012001200

0000 500500500500 1000100010001000 1500150015001500 2000200020002000

ANNUAL TONNAGE kTpaANNUAL TONNAGE kTpaANNUAL TONNAGE kTpaANNUAL TONNAGE kTpa

TIP

PIN

G D

EP

TH

BE

LOW

SU

RF

AC

E m

etre

sT

IPP

ING

DE

PT

H B

ELO

W S

UR

FA

CE

met

res

TIP

PIN

G D

EP

TH

BE

LOW

SU

RF

AC

E m

etre

sT

IPP

ING

DE

PT

H B

ELO

W S

UR

FA

CE

met

res

ShaftShaftShaftShaft Shaft ProjectsShaft ProjectsShaft ProjectsShaft Projects ConveyorConveyorConveyorConveyor

Electric TruckElectric TruckElectric TruckElectric Truck Electric Truck ProjectsElectric Truck ProjectsElectric Truck ProjectsElectric Truck Projects Diesel TruckDiesel TruckDiesel TruckDiesel Truck

Diesel Truck ProjectsDiesel Truck ProjectsDiesel Truck ProjectsDiesel Truck Projects CANNINGTONCANNINGTONCANNINGTONCANNINGTON CADJEBUTCADJEBUTCADJEBUTCADJEBUT

SHAFT DOMINANTSHAFT DOMINANTSHAFT DOMINANTSHAFT DOMINANT



4

Recent Truck Studies

• Callie Project (Normandy). • Kanowna Belle Project (North). • Ridgeway Project (Newcrest). • General confirmation that a hoisting shaft is difficult to justify economically to depths of 800m or more and mining rates to

1.5Mtpa. • New truck technology will potentially extend these limits or further improve the advantage of trucking over hoisting.

Haulage Options Single Decline Truck Haulage.

• Multi-Purpose, cost effective particularly for short life operations. Twin Decline Truck Haulage.

• Similar to above with minimised trucking delays. • Larger possible fleet sizes and higher production rates. • In some instances where shaft hoisting is not economically feasible, and where a single decline limits production capacity,

there is an economically justifiable case for twin decline haulage. Shaft Hoisting.

• Provides high production rates particularly from deep operations. • High initial capital outlay.

Haulage Method Selection; Influencing Factors

• Ore reserve, production rate, mining method & ground conditions. • Depth of orebody below surface/portal. • The need for a decline for service access. • Development schedule and planned mine life. • Vertical and lateral advance rates and coverage required with respect to the size and shape of the orebody and production

rate. • The type and condition of existing infrastructure (ie exploration shafts/declines) and their potential utilisation. • Haulage distances to the shaft. • Ventilation requirements/capacity.

Trucking Technology

• 50 tonne payload capacity diesel trucks have become the benchmark for high production underground mining operations. • These trucks are capable of reliably hauling up a 1 in 7 decline at approximately 9 km/h. • Computer management systems for engines and drivelines and other advancements have; • Reduced fuel consumption and emissions, whilst increasing power outputs. • Reduced down time, increased servicing/rebuild intervals and lower operating costs. • Future trucking improvements will include greater payloads (60 to 80t), more powerful fuel efficient diesel engines, greater

ramp haulage speeds, lower down times, increased service rebuild intervals and better ergonomics. New Generation Trucks Representative makes and models;

Truck Type Model Engine Nominal Capacity

Rigid Body Diesel Elphinstone 73 D 509kW 52.2t

Articulated Body Diesel Wagner MT5000 485kW 50t

Articulated Body Electric Kiruna K1050E 410kW rms 650kw (30min) 50t

Diesel Ramp Truck Tamrock 1000kW 80t



5

Decline Gradient

• No advantage flatter than 1 in 8. • Modern trucks comfortable on 1 in 7, but rear-wheel drive trucks cause more road damage in difficult floor conditions. • Articulated trucks capable of up to 1 in 5 without adverse cycle times. • Truck maintenance costs increase steadily with increasing gradient. • Road maintenance becomes more difficult and costly with increasing gradient and may become impractical at steep grades

with water inflows. • Safety hazard may increase with gradient. • Some states apply shaft rules at steep gradients.

Operating Costs Direct operating costs from first principles for fleet hauling from 550m below portal

Make Model $/t Note Wagner MT5000 3.4 Low profile

Elphinstone 73D 3 Additional decline capital required

Kiruna K1050E 2 Retard problems at this duty. Cost asumes very cheap grid power.

Tamrock Ramp Truck 1.7 In development Practical Constraints on Shaft Decision

• Environmental issues (carbon, energy etc). • Occupational Health and Safety. • Option for increased mining rate and depth with further discovery.

Simulation Modelling

• AMC has developed a multi-use simulation software, which is capable of modelling ‘real life’ circumstances including truck and shaft haulage systems.

• The simulation allows dynamic interaction and modelling of the entire ore handling system from the stope to the concentrator and beyond if required. Some parameters modeled are;

Fleet size, type, performance characteristics, loads, speeds, break downs, maintenance, utilisation, delays, passing, loading, availability of ore, other traffic

• The simulation allows evaluating and quantifying of alternative mine layouts, passing bay distances, location of ore sources, ore/waste/fill tipping and sources, impact of surge capacity, instantaneous handling rates required and queuing of LHD’s.

Simulation Modelling

• Simulation allows the optimisation of each haulage function to operate on the system availability/capacity rather than its individual. Hence significant cost benefits and increased outputs can be achieved by identifying and alleviating limiting factors.

• Similarly, shaft hoisting, including any trucking and conveyor components can be simulated for optimisation of output.



6

Screen captures from within “Areana” a software-modelling package



7



8

Daily Ore Tonnes Hauled

0

1,000

2,000

3,000

4,000

5,000

6,000

0 2 4 6 8 10 12 14

Total Truck Fleet

Dai

lyTo

nnes

Tipp

ed

Average Total Production

5% Chance of GreaterProduction10% Chance of GreaterProduction25% Chance of GreaterProduction75% Chance of GreaterProduction90% Chance of GreaterProduction95% Chance of GreaterProductionTarget

Truck Fleet Availability and Utilisation

0%

20%

40%

60%

80%

100%

8 10 12 14

Total Truck Fleet

Prop

ortio

n of

Tim

e

Break Down

ScheduledMaintenanceServicing

Work Break

Waiting for job

Queued

Delayed

Working

Documents

Selecting Shaft or Decline