d2.5 performance indicators

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Key performance indicators EEQ-S&B-WP2-2.5

(Augus t 2011) Page 1 of 18

KEY PERFORMANCE INDICATORS

Author :Michalis PainesisContributor:S&B Industrial MineralsProject acronym:EE-QUARRY Project.Grant Agreement No:

Issue Date: August

Deliverable Number: D 2.5

WP Number: WP 2

Status : Finished

DISEMINATION LEVEL

X PU= Public

PP= Restricted to other programme participants (including the JU)RE= Restricted to a group specified by the consortium (including the JU)

CO= Confidential, only for members of the consortium (including the JU)


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Document History

Version Date Author Description

1st 20/07/11 Michalis P. 1stDraft

2nd 28/07/11 Michalis P. 2ndDraft

3rd 15/08/11 Michalis P Final Version

Disclaimer

The information proposed in this document is provided as a generical explanation on theproposed topic. No guarantee or warranty is given that the information fits for any particular

purpose. The user thereof must assume the sole risk and liability of this report practicalimplementation.The document reflects only the authors views and the whole work is not liable for any empiricaluse of the information contained therein.


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SUMMARY

This document is the deliverable D2.5 of the WP 2 of the EE-QUARRY Project Develop of a new

and highly effective modeling and monitoring Energy Management System technique in order toimprove Energy Efficiency and move to a low CO2 emission in the energy intensive non-metallicMineral industry.The scope of this document is to identify the Key Performance Indicators, mainly frombibliographical sources, that could be used to examine the efficiency of the production process.Our focus will be mainly on the Key Performance Indicators related with energy consumptionefficiency.


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CONTENTS

SUMMARY .................................................................................................................................... 3

CONTENTS ................................................................................................................................... 4

ABBREVIATIONS ......................................................................................................................... 5

INTRODUCTION ........................................................................................................................... 7

1 KEY PERFORMANCE INDICATORS ................................................................................... 8

1.1 PRODUCTION RATE .................................................................................................... 8

1.2 YIELD ............................................................................................................................ 8

1.3 OPERATIONAL AVAILABILITY ..................................................................................... 8

1.4

EQUIPMENT UTILIZATION ........................................................................................... 9

1.5 STRIPPING RATIO ........................................................................................................ 9

1.6 SPECIFIC CO2 (KG CO2 PER MT OF PRODUCT) ...................................................... 9

1.7 ENERGY USE (MJ PER MT OF PRODUCT) .............................................................. 13

1.8 SPECIFIC EXPLOSIVES CONSUMPTION ................................................................. 13

1.9 THE KPI FOR PERLITE AND BENTONITE FOR THE YEAR 2010 ............................ 14

CONCLUSIONS .......................................................................................................................... 15

REFERENCES...........................................................................................................................16

ATTACHMENTS .......................................................................................................................... 17


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ABBREVIATIONS

EE-QUARRY

Develop of a new and highly effective modeling and monitoring Energy Management Systemtechnique in order to improve Energy Efficiency and move to a low CO2emission in the energyintensive non-metallic mineral industry.

WP CO2-e

Work Package Carbon dioxide emissions

S/T GHG

Scientific and Technical Green House Gases

KPI

Key Performance Indicator

MT

Metric Ton


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LIST OF TABLES

Table 1. Industr ial Processes emiss ion factors for explosive use Source: AGO 2006a. ...... 9

Table 2 Emission Factors for Calculating CO2 Emissions Generalized Approach .......... 12

Table 3 Nationaland European emissionfactorsforconsumed electricity .......................... 12

Table 4 Conversion factor energy uni ts to MJ ........................................................................ 13

Table 5 KIPs perl ite and bentonite for 2010 ............................................................................ 14


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INTRODUCTION

Key Performance Indicators are a set of quantifiable measures, agreed to beforehand, that a

company or industry uses to gauge or compare performance in terms of meeting their strategic

and operational goals. KPIs vary between companies and industries, depending on their priorities

or performance criteria. Also they are referred as "key success indicators (KSI)".

In our case that we are talking about quarries the KPIs are related to productivity, energy

consumption and cost efficiency. Companies face numerous challenges, both in selecting

appropriate KPIs at the company level and in implementing the selected KPIs at the operational

level.


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1 KEY PERFORMANCE INDICATORS

1.1 Production Rate

Production rate is the number of goods that can be produced during a given period of time.Alternatively, the amount of time it takes to produce one unit of a good.In mining, most commonly, the production rate is expressed in MT/h or m3/hour.

1.2 Yield

Yield is the quotient of the saleable or useful product expressed in MT to the quantity of extractedmaterial. For example if from 100 MT of extracted material, the saleable grade is 75 MT, the yieldis 75%. Sometimes yield is also called Non-product output and it is expressed in MT of Wasteper MT of product.

1.3 Operational availability

Operational availability is a measure of the average availability over a period of time and it

includes all experienced sources of downtime, such as administrative downtime, logistic

downtime, etc. It is the probability that an item will operate satisfactorily at a given point in time

when used in an actual or realistic operating and support environment. It includes logistics time,

ready time, and waiting or administrative downtime, and both preventive and corrective

maintenance downtime. It is essentially the a posteriori availability based on actual events that

happened to the system.

Operational availability is the ratio of the system uptime and total time. Mathematically, it is given

by:

Where the operating cycle is the overall time period of operation being investigated and uptime is

the total time the system was functioning during the operating cycle. Operational availability is

required to isolate the effectiveness and efficiency of maintenance operations. It is the actual

level of availability realized in the day-to-day operation of the facility. It reflects plant maintenance

resource levels and organizational effectiveness. Operational availability is required to isolate the

effectiveness and efficiency of maintenance operations.


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1.4 Equipment Utilization

Equipment Utilization is defined as the percentage of PLANT OPERATING TIME (C) during

which equipment is in production, that is, production is not prevented by equipment malfunction,

operating delays, or scheduled downtimes.

1.5 Stripping ratio

The main characteristic employed in economic evaluation of open pit mining is the Stripping ratio

(SR) Stripping ratio is the volume of removed waste- overburden per unit of mineral. Usually it is

expressed in m3 of overburden per MT or m3 of ore. It is obvious that a large stripping ratio is

less economical than a small one, because more rock must be moved for a certain amount of

revenue generating ore.

1.6 Specific CO2 (kg CO2 per MT of product)

One of the most commonly used indicators in order to monitor energy efficiency is the Specific

CO2 which is the kg of CO2 emitted for the production of 1 MT of product.

Data from Aggregate industries in UK indicate comparable specific CO2 at between 4,0-5,0

kg/MT. In a quarry operation we can distinguish 3 groups by means of CO2 emissions:

a) CO2-e occurring during blasting

The use of explosives in mining leads to the release of greenhouse gases. The activity

level is the mass of explosive used (MT). Emissions are calculated using the EFs from

Emission factor

Explosive typeMT CO2/ MT explosive

ANFO0.17

Heavy ANFO 0.18

Emulsion0.17

Table 1. Industrial Processes emission factors for explosive useSource: AGO 2006a.


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b) CO2-e occurring by the combustion in diesel fuel operating vehicles or/and

generators. That called also Direct emissions from Combustion sources

CO2 production from combustion is a fairly straightforward process, at least in theory. A

reaction between carbon in any fuel and oxygen in the air proceeds stoichiometrically. Forevery 12 kg of carbon burned, there is combustion (a chemical reaction) which results in 44

kg of CO2, or a net mass multiplier of 3.67. There are two basic approaches for estimating

direct CO2emissions:

Direct measurement and calculation based method.

Direct measurement of CO2-e is performed through the use of a Continuous Emissions

Monitoring System (CEMS). Calculation based method is a mass balance approach where the

carbon content and carbon oxidation factors are applied to the fuel input levels to determine

emissions. Most commonly it is used the calculation based method and especially thegeneralized approach.

The generalized emission factors are reported in terms of mass of CO2per unit of fuel energy or

per unit of mass or volume. Table 2 lists emission factors for different fuel types.

Emission Factors for Calculating CO2 Emissions Generalized Approach

Fuel Type CO2 Emission Factor CO2 Emission Factor

Fossil Fuel CombustionCoal and Coke kg CO2/MMBtu kg CO2/tonAnthracite Coal 103.62 2,599.83Bituminous Coal 93.46 2,330.04Sub-bituminous Coal 97.09 1,674.86Lignite 96.43 1,370.32Unspecified (residential/commercial) 95.33 2,012.29Unspecified (industrial coking) 93.72 2,462.12Unspecified (other industrial) 93.98 2,072.19Unspecified (electric utility) 94.45 1,884.53

Coke 113.67 2,818.93Natural Gas (by Higher Heating Value) kg CO2/MMBtu kg CO2/scf975 - 1,000 Btu/scf 52.56 Varies1,000 - 1,025 Btu/scf 52.91 Varies1,025 - 1,050 Btu/scf 53.06 Varies1,050 - 1,075 Btu/scf 53.46 Varies1,075 - 1,100 Btu/scf 53.72 Varies> 1,100 Btu/scf 54.71 VariesU.S. Weighted Average (1,029 Btu/scf) 53.06 0.0546

Petroleum Products kg CO2/MMBtu kg CO2/gallonAsphalt and Road Oil 75.61 11.95Aviation Gasoline 69.19 8.32

Distillate Fuel Oil (#1, 2, and 4) 73.15 10.15Jet Fuel 70.88 9.57Kerosene 72.31 9.76


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LPG (average for fuel use) 63.16 5.79Propane 63.07 5.74Ethane 59.58 4.14Isobutene 65.08 6.45n-Butane 64.97 6.70

Lubricants 74.21 10.72

Motor Gasoline 70.88 8.81Residual Fuel Oil (#5 and 6) 78.80 11.80Crude Oil 74.54 10.29

Naphtha (401

oF) 73.15 10.15

Pentanes Plus 66.88 7.36Petrochemical Feedstocks 71.02 9.18Petroleum Coke 102.12 14.65Still Gas 64.20 9.17Special Naphtha 72.82 9.10Unfinished Oils 74.54 10.34

Waxes 72.64 9.58Waste Tires kg CO2/MMBtu kg CO2/tonWaste Tires 112.84 3,159.49

Non-Fossil Fuel CombustionNon-Fossil Fuels (solids) kg CO2/MMBtu kg CO2/tonWood and Wood Waste (12% moisture) 93.87 1,443.67Kraft Black Liquor (North American 94.41 1,130.76

Kraft Black Liquor (North American 95.13 1,164.02

Non-Fossil Fuels (Gas) kg CO2/MMBtu kg CO2/scf

Landfill Gas (50% CH4/50% CO2) - 502.50 52.07 0.0262

Wastewater Treatment Biogas 52.07 VariesSource: The Climate Registry (TCR) General Reporting Protocol, Version 1.0, March 2008, Table 12.1

(http://www.theclimateregistry.org/downloads/GRP.pdf); USEPA Climate Leaders GHG Inventory Protocol

Alternative Fuels1

kg CO2/MMBtu kg CO2/galAnimal Fat 74 9.2Waste Oil 74

Plastics 75Solvents 74Impregnated Saw Dust 75Other Fossil based wastes 80Dried Sewage Sludge 110Mixed Industrial waste 83Municipal Solid Waste 90.652

1. Source of data for Alternative Fuels is primarily the EPA Proposed Greenhouse Gas Reporting

Rule, Table C-2, of Subpart C. These values are subject to change when EPAs final rule is in

effect. http://www.epa.gov/climatechange/emissions/downloads/GHG_Rule/RulePart98A-P.pdf

Note the units of the Emission factor in Table C-2 are in kg CO2/MMBtu.

2. DAQ is assuming Animal Fat can be treated as waste oil. Input-based emission factor calculated askg CO2/gal based on heating value of 124,586 Bt/gal. Source:


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Table 2 Emission Factors for Calculating CO2 Emissions Generalized Approach

c) Indirect CO2 emissions, equivalent for every Kwh of electricity consumed.

Indirect CO2emissions are emissions that are consequences of the activities of the company

(quarry) but occur at sources owned or controlled by another company.

Each European country uses a different mix of fuels to produce electricity, or exploits renewable

energy sources in different level and therefore each country has a different conversion factor in

order to calculate the CO2e that correspond to every Kwh. At the following table 3, are

presented the European and National emission factors for electricity consumption.

Country Standardemission factor

(MT CO2/MWhe)

LCA *emissionfactor

(MT CO2-eq/MWhe)

Austria 0.209 0.310Belgium 0.285 0.402Germany 0.624 0.706Denmark 0.461 0.760Spain 0.440 0.639Finland 0.216 0.418France 0.056 0.146UnitedKingdom 0.543 0.658Greece 1.149 1.167Ireland 0.732 0.870Italy 0.483 0.708Netherlands 0.435 0.716Portugal 0.369 0.750Sweden 0.023 0.079Bulgaria 0.819 0.906Cyprus 0.874 1.019CzechRepublic 0.950 0.802Estonia 0.908 1.593Hungary 0.566 0.678Lithuania 0.153 0.174Latvia 0.109 0.563

Poland 1.191 1.185Romania 0.701 1.084Slovenia 0.557 0.602Slovakia 0.252 0.353EU-27 0.460 0.578

Table 3 Nationaland Europeanemissionfactorsfo rconsumedelectricity

(A life cycle assessment (LCA, also known as life cycle analysis, ecobalance, Cradle to grave analysis) is atechnique to assess environmental impacts associated with all the stages of a product's life from-cradle-to-grave (i.e.,

from raw material extraction through materials processing, manufacture, distribution, use, repair and maintenance,

and disposal or recycling). LCAs can help to avoid a narrow outlook on environmental concerns)


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1.7 Energy Use (MJ per MT of product)

This indicator is very important to evaluate the energy efficiency of our process.

Gross calorific (high heat value) of fuels shall be used to convert energy units to MJ (see table 4).

In case of use of other fuels, the calorific value used for the calculation should be indicated. The

use of explosives should be included in the figure for total energy consumption. Electricity means

net imported electricity coming from the National grid and internal electricity generation measured

as electric power.

Fuel Quantity Units Conversion

factor

Energy (MJ)

Natural gas kg 54.1

Natural gas Nm3 38.8

Propane kg 50.0

Butane kg 49.3

Kerosene kg 46.5

Gasoline kg 52.7

Diesel kg 44.6

Gas oil kg 45.2

Heavy fuel oil kg 42.7

Dry steam coal kg 30.6

Anthracite kg 29.7

Charcoal kg 33.7

Industrial coke kg 27.9

Electricity kWh 3.6

Table 4 Conversion factor energy uni ts to MJ

1.8 Specific Explosives consumption

Specific explosives consumption is the kg of explosive used to extract 1 MT or m3of material

(ore, overburden etc). The specific explosives consumption depends heavily on type or rock and

the type of the explosive itself.


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1.9 The KPI for Perlite and Bentonite for the year 2010

Table 5 KIPs perlite and bentonite for 2010


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CONCLUSIONS

Choosing the right KPIs is reliant upon having a good understanding of what is important to the

organization. During last years for the mining business sustainability and energy efficiency

became an increasingly important factor. Next to the traditional KPIs were introduced new

indicators and energy information systems. However all the management systems based on KPIs

can become unusable without careful consideration of what data to collect, how often to collect it

and how to present and decode the data collected.


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REFERENCES

Mining Engineering Handbook Howard Hartman The Climate Registry (TCR) General

Reporting Protocol, Version 1.0, March 2008.-

The Control of energy consumption and the investigation of CO2 emissions in the

production of aggregates (Basketin, Adiguzel, Tuylu, Istanbul University , Faculty of

engineering , Dpt of Mining engineering 2010).

A management System of energy (Georgia Tech).

European Environment Agency .


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ATTACHMENTS

a. Deliverable review report

Date Venue

Reviewer

Company

b. Technical result of the deliverable

Deliverable covers the topic specified in the tit le

Yes Partly No

Technical contents are relevant to EE-QUARRY and to the WPs

Yes Partly No

Presented results in the deliverable are of high value

Yes Partly No

Technical sound o f the deliverable

Good Regular Bad

Described work in the deliverable follows a clear methodology

Good Regular Bad

Please add your comments on the content and the technical results of the deliverable. Pleasecomment the problems, if any.

Comments:


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c. Length, structure and presentation of the deliverable

Adequate length of the deliverableGood Regular Bad

Deliverable organization is appropriate

Good Regular Bad

Presentation of the deliverable clear and concise

Good Regular Bad

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:

d. Rating for the deliverable

Please provide a rating for this deliverable from 5 (excellent) to 1 (very poor): ____

Deliverable is

AcceptedAccepted

withrevisions

Rejectedunless

modifiedas

suggested

Rejected

Comments:

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