d2.5 performance indicators
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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
Please add your comments on the length, the structure and the presentation.Comments
:
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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