Alessio Arata

7/30/2019 Alessio Arata

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Comminution process optimisationthrough reliability and maintainability

modelling and simulation

Alessio Arata

Esteban Heidke

Adolfo ArataFredy Kristjanpoller


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Paper motivation


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An integral engineering approach

ENGINEERING SHOULD BE INTEGRATED WITH OPERATIONS, SINCE LIMITING THE

FOCUS ON THE FORMER HINDERS THE EFFICIENCY OF THE LATTER

OPTIMIZING INVESTMENTS EARLY DURING PROJECT DEVELOPMENT IS MORE

PROFITABLE AND EFFECTIVE

THE EVALUATION OF AN INVESTMENT PROJECT SHOULD OCCUR DURING THE

ENTIRE ENGINEERING DEVELOPMENT PROCESS

THE TRADE-OFFS SHOULD BE SUPPORTED BY FINANCIAL TOOLS USING THE COST

BENEFIT CRITERIA

ENGINEERING SHOULD BE SUPPORTED BY PROBABILISTIC TOOLS THAT ENABLES

THE RISKS TO BE QUANTIFIED

ENGINEERING SHOULD HAVE A BOTTOM-UP APPROACH CAPABLE OF IDENTIFYING

CRITICALITIES AT THE MICRO LEVEL (EQUIPMENT) TO QUANTIFY THE IMPACTS AT AMACRO LEVEL (BUSINESS)

RELIABILITY ENGINEERING IS THE TOOL WHICH PUTS INTO PRACTICE PROJECT

ANALYSIS FROM AN LCC PERSPECTIVE


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Objective


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The objective of this paper is to develop a methodology, using RAM modelling and a

simulation of the processes to enable projects to be appraised and optimised in their

feasibility study phase. Thus, a Life Cycle Cost approach will be used to evaluate the effect ofchanges on the flow sheet and the capacity of equipment and storage systems in order to

assess the business impact of proposed modifications and select the best combination, taking

into account expected production and required investment.

Paper objective

In a comminution process:

a) Identify critical and bottleneck equipment.

b) Determine the optimal capacity of storage systems (stockpiles, bins).

c) Indentify improvement opportunities with impact on the production level.

d) Identify saving opportunities.

e) Determine the risk and certain level in achieving the target values.f) Evaluate the different improvement scenarios.

g) Identify through optimisation the best combination of improvements that maximizes NPV.


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Reduction in investment costs

Low redundancy

Less reliable and maintainable equipment

Limited design capacity

Reduction in failure cost and operating costs

Increased availability (greater redundancy and reliability)

Improved asset management

Efficient management of third parties and spare parts

Cost

Investment

Operating andfailure costs

Total Cost

Reliability engineering in life cycle cost analysis (LCC)

investment (CAPEX)

global operating cost

(OPEX)

Failure cost in the project Life Cycle Cost (LCC)

failure cost

Optimum

Level of reliabilityand maintainability


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Some general concepts


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RBD Modelling

Serie

Paralelo

Stand-by

Redundancia

parcial

Fraccionamiento

L

ogical-functional

configurations

Serie

Parallel

Stand-by

k/n

Share

load


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Stockpile and bins modelling

Stockpilesim

ulation

Availability downstream

upstream downstream

Q stockpile and availability downstream

Stockpile

upstream UP; q stockpile > 0 --> downstream UP

upstream DOWN; q stockpile > 0 --> downstream UP

upstream DOWN; q stockpile = 0 --> downstream DOWN


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General methodology


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RAM otimisation in the engineering process

RAM approachDiseo de PDF

Mass and energybalance

Nominal sizing of

processes

Preliminary

equipment list

RAM simulation of

processes

Criticity and sensivity analysis

Optimisation to determine

best combination of cases

that maximase NPV

Identification of improvement

and saving opportunities

Estimate of the

expected procuction

Equipment capacity

Idle capacity

Stock-pile and bins capacity

LCC valuation of

cases

(capex, opex y prod.)

Optimal alternative

Iterationof cases


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Processsurvey

Obtaining andvalidating shutdowndata

Logical-functionalconfiguration ofthe process

RAM analysis Equipment

Capacities

Process flow-sheet

Design criteria

Process flows

Redundancies

Logical-functional modeling of the system and

validating the configuration

Behavior of the process in the face of faultsand shutdowns of equipment and sub-systems

Incidence of stock-piles in the process

Simulation of production, reliability,

maintainability and availability of the

base and improved cases

Monte Carlo and risk simulation

Optimum dimensioning of stock-piles Identification of opportunities for

improvement under the LCC approach

Criteria of experts / engineering In-put from vendors

Historical data for maintenance

and production

Understanding

Benchmarking

ModelingSimulation

LCC Valuation

LCC evaluation of scenarios

Simulation and optimization to identify the best

combination of improvement opportunities

LCC prioritization of alternatives

Optimization toselect the bestscenario

Engineering design optimisation stages


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Development and main results


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Process understanding and data

General process diagram

74 pieces of equipment, 8732 notices: operational unplanned detentions, unplanned

maintenance interventions, planned maintenance interventions.

Summary of historical information of detentions

Date Time [hr] Duration [hr] Type Equipment

01-01-2010 11:38 5.35 MCM EQUIPMENT-1

01-01-2010 11:45 4.2 DO EQUIPMENT-2

06-01-2010 6:18 40.6 MP EQUIPMENT-3


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Process understanding

Cap. Carga viva: 100.000 [t]Cap. Carga viva: 100.000 [t]

Cap. Carga viva: 80.000 [t]

Cap. Carga viva: 80.000 [t]

(3)

(3)

(3)

(2)

(6)

(6)

(6)

(2)

(2)

(1)

(6)

(1)

(6)

(3)

(6)

(1)

(10) (10)

(1)

(5)

(5)

(5)

(6)

(6)

(*) # Pieces of Equipment

A

B

F

C

E

D

GH

I

J

K

L

N

MX Mass Flow

Process flow-sheet diagram

Equipment #

Primary crusher 3

Secondary crusher 6

HPGR 6

Ball mill 5


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Modelling

Grinding

Feeder

Screen

Pump

Hydrocyclone

S

F S

S

S

S

F S

S

S

S

F S

S

S

S

F S

S

S

S

F S

S

S

F

S

Grinding

Conveyor belt

Mill

S

F

Serie

Share load


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Processes results

Secondary crusher availability


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Criticity analysis

ndice Equipo1 Correa Sp L2

2 Correa Recir. 23 Feeder 6

4 Correa 6

5 Harnero 6

6 Feeder 4

7 Correa 4

8 Harnero 4

9 Feeder 510 Correa 5

11 Harnero 6

12 Correa Sp L113 Correa Recir. 1

14 Feeder 1

15 Correa 1

16 Harnero 117 Feeder 2

18 Harnero 2

19 Correa 2

20 Feeder 3

21 Correa 3

22 Harnero 3

23 Correa a Chancadores

24 Chancador 1

25 Chancador 226 Chancador3

27 Chancador4

28 Chancador5

29 Chancador6

30 Co rrea material chancado

LeyendaGrfico de criticidad

Identification of critical equipment


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Improvement opportunities tertiary crusher

98,4%

98,8%

99,2%

0 50 100 150

-

Incorporation of idle capacity in

the HPGR crusher, from 51.82%to 65% each.

Incorporation of a conveyor

belt to the discharge of

material over the downstreamstockpile, parallel to the

existing one.

Improvement 2 & 3.

A

vailability

Corrected

utilization

Improvement 1Base Situation Improvement 3Improvement 2

95,5%

96,5%

97,5%

98,5%

0 50 100 150

98,5%

99,0%

99,5%

100,0%

0 40 80 120

96,0%

97,0%

98,0%

99,0%

0 40 80 120

98,5%

98,7%

98,9%

99,1%

99,3%

99,5%

0 40 80 120

96,0%

97,0%

98,0%

99,0%

0 40 80 120

98,5%

99,0%

99,5%

100,0%

0 40 80 120

96,5%

97,5%

98,5%

99,5%

0 40 80 120

Av

ailability

Utiliz

ation

Base case Improved case 1 Improved case 2 Improved case 3


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Illustrative results

Process availability for different alternatives

99,87% 99,79% 99,88%

99,89%99,91% 99,87% 99,75% 99,84%

98,00% 98,20% 97,86%98,41%

98,84%

97,95%97,94% 97,97%

99,26%99,44% 99,24%

99,47%99,47% 99,21%

98,65%98,75%

94,61%

91,84%

94,61%

95,49%

93,85%

96,40% 96,40%

91,00%

94,00%

97,00%

100,00%

0 1 2 3 4 5 6 7 8

Availability[%]

Alternatives

Ch. Primario Ch. Secundario

Ch. Terciario MoliendaGrinding

Secondary Cr.

Tertiary Cr.

Primary Cr.


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Main results and conclusions


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Main results

Resumen de capital fijo para las distintas situaciones por etapa

Price of Cu conc.

ProcessesScenario

Stockpile

CapacityScenario

Stockpile

CapacityScenario

Stockpile

CapacityScenario

Stockpile

CapacityScenario

Stockpile

CapacityScenario

Stockpile

Capacity

Primary Cr. Base 50.000 Base 50.000 Base 50.000 Base 50.000 Imp. 1 50.000 Imp. 1 50.000

Secondary Cr. Imp. 3 10.000 Imp. 3 10.000 Imp. 3 20.000 Imp. 3 10.000 Imp. 3 20.000 Imp. 3 40.000

Tertiary Cr. Base 10.000 Base 10.000 Base 10.000 Imp. 2 20.000 Base 10.000 Base 10.000

Grinding Imp. 4.b - Imp. 4.b - Imp. 4.b - Imp. 4.a - Imp. 4.b - Imp. 4.b -

1,5 [US$/lb] 2,0 [US$/lb] 2,5 [US$/lb] 3,0 [US$/lb] 3,4 [US$/lb]2,5 [US$/lb] *

Price of Cu.

Concentrate

Systemic

Corrected

Utilization

CAPEX

[bUS$]

OPEX

[bUS$]

Annual

estimated

sales

[bUS$]

NPV

[bUS$]

Annual

estimated

sales

[bUS$]

NPV

[bUS$]

NPV increase

over the base

case

CAPEX

decrease of

project over

the base case

Cash flowsincrease over

the base case

(in present

value)

1,5 [US$/lb] 91,75% 1,98$ 0,67$ 1,23$ 0,18-$ 1,09$ 1,05-$ 0,87$ 0,13$ 0,74$

2,0 [US$/lb] 91,75% 1,98$ 0,67$ 1,64$ 2,81$ 1,45$ 1,60$ 1,21$ 0,13$ 1,08$

2,5 [US$/lb] 92,00% 1,99$ 0,67$ 2,06$ 5,81$ 1,82$ 4,25$ 1,56$ 0,12$ 1,45$

2,5 [US$/lb] * 90,91% 1,98$ 0,66$ 2,03$ 5,68$ 1,82$ 4,25$ 1,43$ 0,12$ 1,31$

3,0 [US$/lb] 92,11% 2,00$ 0,67$ 2,47$ 8,80$ 2,18$ 6,89$ 1,91$ 0,11$ 1,80$

3,4 [US$/lb] 92,33% 2,02$ 0,67$ 2,81$ 11,21$ 2,47$ 9,01$ 2,20$ 0,09$ 2,11$

Optimized Cases Base Cases


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Conclusions

This paper proposes a methodology for optimising processes through

reliability engineering using a LCC (Life Cycle Cost) perspective, which enables the

effect on expected production of a change in the processes reliability to be

quantified and the best combination of improvements considering the increase or

decrease in capex involved in each new scenario to be determined.

Thus it incorporates a new decision variable to enable the profitability of anew investment project to be maximized.

In this case in particular, for an assumed copper concentrate price of

US$2.5/lb, the methodology enables net increases in NPV of up to US$1.6 billion,

including US$117 million due to decreased CAPEX and US$1.4 billion due toincreased production over the life of the project, estimated at 25 years.


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Alessio Arata

Esteban Heidke



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Appendixes


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R-MES

EXCEL

CRYSTALBALL

Historical data ofdetentions of equipment

Design and operationcriteria

Flowchart of ProcessModelling the processes

RAM simulationof the base

situation

Get the RAMindicators of the

process

Sensitivity the indicators basedon the stockpiles capacity

Identify thecritical

equipment

Incorporating theimprovementopportunities

RAM simulation ofthe improvement

scenarios

How?Sw R-MES

Expertcritera

Is it necessary to

improve a new case?(Expert criteria)

Yes

Summary RAM indicators of theprocesses (base and improved)

No

CAPEX, OPEX andWilliams index of equipment

Flowcharts of all cases(base and improved)

Valuing the flowcharts(CAPEX of the baseand improved cases)

Economic andenvironment variables

Generate all possible combinationsbetween process stages

LCC Evaluatingscenarios combined

Identify the combinations thatmaximize the business benefits

Detailed methodology


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Escalamiento

Proceso Slido

Costo directo

Equipos de proceso sin instalar 100%Costo de instalacin 45%

Instrumentacin 9%

Caerias 16%

Instalacin elctrica 10%

Edificis 25%

Urbanizacin 13%

Instalaciones auxliares 40%

Terreno 6%

Total Costo directo 264%

Costo indirecto

Ingeniera y Supervicin 33%

Gastos de construccin 39%

Total Costo indirecto 72%

Total Costos directos e indirectos 336%

Utilidad contratistas 17%

Contingencias 34%

Total Capital Fijo 387%

Se llama economa de escala al procesomediante los costos unitarios de

produccin disminuyen al aumentar la

cantidad de unidades producida

Mtodod

eLang

Escalamiento de Williams

l


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Valuation parameters

Variable Cantidad Unidad Ley del mineral 0,58% [Cu/material]

Tiempo de operacin anual 365 das

Horizonte de evaluacin 25 aos

Costos operacionales 0,55$ [US$/lb concentrado de Cu]

Costos fijos 215.000.000,00$ [US$/ao]

Tasa de retorno 10% -

Costo de acopio de material 1.000,00$ [US$/t acopiada de carga viva]Capital de trabajo 810.000.000,00$ [US$]

Depreciacin lineal 10 [aos]

Capacidad instalada 191.520 [T material promedio diario]

Variable Cantidad Unidad

Precio del concentrado de Cobre 3,40$ [US$/lb concentrado de Cu]

Impuesto a la renta 17% -

Impuesto especifico: Royalty 5% -

Impuesto por retiro de utilidades 18% -

Variables econmicas a considerar para la evaluacin LCC


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A por proceso para distintos casos combinados

95,88%

97,87%

96,39%97,14%

88,26%

96,78%

99,93%

97,47%

99,19%

98,03%

98,80%

95,24%

88,00%

89,50%

91,00%

92,50%

94,00%

95,50%

97,00%

98,50%

100,00%

Primario Primario +

Stockpile

Secundario Secundario +

Stockpile

Terciario Terciario +

Stockpile

Molienda

Disponibilid

adAcumulada[%]

Proceso

Caso Base

Caso mejorado 1

Base case

Improved case


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Alessio Arata

Esteban Heidke


Alessio Arata

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