2xEP Mining Sector

Doubling Australia’s energy productivity by 2030 Re-energising the mining sector to improve its competitiveness

10 June 2015 Consultation Draft (Version 1.3)

2xEP Mining Sector Overview

Thanks The Board and staff of the Australian Alliance to Save Energy (A2SE) gratefully acknowledge our colleagues Jonathan Jutsen, Anita Stadler, Fiesal Musa (Energetics) and Michael Smith (Energy Change Institute at the Australian National University) as the primary researchers and authors of this text. We also acknowledge the considerable intellectual and practical contributions of Sarah Boucaut of the Coalition for Eco Efficient Comminution (CEEC) and Mary Stewart of Energetics and CEEC. This work has been supported by financial contributions to various components of the Australian Energy Productivity Roadmap project made by the Commonwealth Department of Industry, the New South Wales Office of Environment and Heritage and the Clean Energy Finance Corporation. This work would not have been possible without the exceptionally generous support of the Institute for Sustainable Futures (ISF) at the University of Technology, Sydney and Energetics. ISF hosts A2SE and the Roadmap project. Energetics provides significant in-kind support, notably through contributions to the project by Jonathan Jutsen, Anita Stadler and Fiesal Musa. We acknowledge our project collaborators: ClimateWorks Australia at Monash University, the Low Carbon Living CRC at the University of New South Wales, the Energy Change Institute at the Australian National University, the Newcastle Institute for Energy & Resources at the University of Newcastle and the Energy Flagship program at CSIRO. Citation: Stadler, A, Jutsen, J., Musa, F. & Smith, M. (2015). Doubling Australia’s energy productivity by 2030: Re-energising the mining sector to improve its competitiveness, Draft Version 1.3. Sydney: Australian Alliance to Save Energy. The views expressed in this text are those of A2SE and not necessarily those of our supporters and partners. We have taken all care to ensure that data is correct. All responsibility for the text rests with us. © Australian Alliance to Save Energy 2014 c/- Institute for Sustainable Futures University of Technology, Sydney Level 11, Building 10  235 Jones Street, Ultimo, NSW 2007 email: [email protected] phone: 02 9514 4948 web: www.a2se.org.au abn: 39 137 603 993


CONSULTATION DRAFT VERSION 1.3

Executive summary Australia’s capacity to capture the next wave of mining investment and to secure future export revenues in an environment of strong supply competition depends critically on regaining national competitiveness. (Minerals Council of Australia, 2014a)

The Australian Energy Productivity (2xEP) Roadmap initiative commenced in July 2014. The Australian Alliance to Save Energy (A2SE) is working on the program with the support of governments, businesses, industry associations and thought leaders from a range of institutions. Energy productivity is a declared policy priority for federal and state governments. Improving energy productivity is about increasing the economic value added per unit of energy used and dollar of energy spent. In a period of rapidly increasing energy prices in Australia, a holistic approach to energy productivity can make a major contribution to Australia’s overall productivity and competitiveness. This report provides an overview of issues that need to be addressed to substantially enhance energy productivity in the mining sector. It also provides a starting point for discussion with stakeholders in the mining sector and the development of the Mining Sector 2xEP Roadmap, to address the opportunities, barriers, policy recommendations and implementation for 2xEP in the mining sector.

Why focus on energy productivity in mining?

Economic productivity in many sectors of the Australian economy, including mining, has been flat or declining in recent years. The long-term decline in base and precious metal ore grade is one of the key drivers of this trend in mining. This also has a direct impact on the energy intensity of production and is therefore the energy productivity of the mining sector. Australia is also amongst the bottom half of all G20 countries with regard to both economic value per unit of energy input and rate of growth in energy productivity (World Bank, n.d.). If the decline in economic and energy productivity is not addressed, Australia’s long-term competitiveness is at risk. Mineral resources are critical to future global development as well as the performance of the Australia’s economy and the living standards of our people. The sector has such a dominant influence on the Australian economy and energy demand that addressing economic (including energy) productivity, without considering developments in the mining sector, would be ineffectual. As illustrated below, the mining sector now accounts for about 11% of GDP. During the recent extended commodity price boom the sector contributed significantly to increased disposable income and employment (BREE, 2014b, Downes, Hanslow, & Tulip, 2014). In fact 50% of national income growth over the period 2002 to 2012 are attributable to factors associated with the commodity price boom (Gruen, 2012).

i


CONSULTATION DRAFT VERSION 1.3 2004 to 2013: Mining’s share of GDP increases* 7.8%

Index, 2012/13 = 100

200

11%

… and  real disposable income by 13% / real wages by 6%  unemployment rate by ≈1.25%

150 100 50 2000-2012: 50% of national income growth due to boomtime factors

0

Base metals prices – A$ Terms of trade

Bulk commodities prices – A$

The commodity price boom supported an increase in the average profit margin of miners from 10% in 2001/02 to 43% in 20011/12. Mining companies increased their capital investment over this period, from 14% of operating cost to an aggregate sector Capex:Opex ratio of 40%. Since then the decline in the commodity prices resulted in a sharp drop in both the aggregate profit margin and Capex:Opex ratio of the sector (ABS, 2014a, 2014d, 2014g; RBA, 2014a). The prevailing market conditions amplify the intrinsic challenge faced by the resources industry, i.e. making long-term capital commitments when medium term revenue projections are volatile at best. Currently, long range price projections suggest that prices will remain subdued for some time as illustrated1 with reference to thermal coal below. Unless Australian sites in the third and fourth quartile move down the production cost curve, the negative impact on the Australian economy, rural communities and investors could be significant (RBA, 2014b; Kannan, 2015).

A lower Australian dollar will not be a major factor as US dollar strength also 1

Cost curves, reproduced from the RBA, August 2014 Statement on Monetary Policy (RBA, 2014b)

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impacts the currencies of other major producers. Given that diesel is a major cost to many mines, the drop in oil prices could improve the performance of sites, but on a per tonne basis the impact on coal (for example) is only expected to translate to a $US1.80 per tonne drop in costs (Macdonald-Smith, 2015). In some regards, the drop in oil prices could make Australian producers less competitive on a CFR-basis (i.e. cost inclusive of freight), pushing them higher up the cost curve. As highlighted in a 2015 Bloomberg report, the drop in bunker fuel prices wiped out the price advantage of leading Australian iron ore producers over Brazil’s Vale SA, which could land a tonne of iron ore cheaper than its Australian rivals in China (Riseborough & Spinetto, 2015). Energy cost can therefore be a determinant of the relative competiveness of Australia’s resource sector on the global stage, especially at a time when global demand is weakening. Energy cost represents between 10–20% of operating cost on most mine sites (Energetics, 2014). At a company level, institutional investors are increasingly taking note of how miners manage their energy (Smith, 2013). However, energy is a manageable cost, with demonstrable savings of 5–30% in energy use across core processes such as comminution and haulage. The mining services, equipment and technologies sub-sector (METS), identified by the Commonwealth as one of the five Australian Industry Growth Centres can be a key competitive differentiator for Australia in the global mining services market (Australian Government, 2014). Investment in energy efficient equipment and processes could have capital and labour productivity benefits. Improved energy productivity also provides a hedge against future price rises, with 100% of diesel, the main energy source in mining, expected to be imported in the near future (Blackburn, 2014). Mining remains a major employer and large energy user, and the response of the sector to improving productivity, including energy productivity, will shape its future competitiveness and, to a large extent, that of Australia.

The 2xEP initiative

In response to these factors, the A2SE 2xEP initiative proposes doubling energy productivity across the Australian economy by 2030 from $222 real GDP (2010$) per unit of energy input (primary energy measured in GJ) in 2010 to $444 in 2030. This target is in line with other major economies, and needs to be achieved to avoid entrenching the competitive disadvantage that has emerged in recent years. At a mining sector level an appropriate 2030 energy productivity target, relative to the current trajectory, needs to be set by the industry. Many mining companies are familiar with targets of this nature, having already set and achieved targets to improve the productive use of energy. For example, BHPBilliton achieved a 15% improvement in energy intensity over the period 2006–2012, exceeding its target of 12% (BHPBiliton, 2014). For companies, an energy productivity target is in many regards ‘easier’ to achieve than an energy efficient equivalent, since some of the improvement is driven by increased value of production output. This is evident from the performance of the mining industry over the recent past as illustrated below (Stadler,2015). In this way the energy productivity metric ‘recognises’ the shareholder value imperative of growing outputs faster than inputs. Since the energy productivity metrics are sensitive to both commodity and energy prices, iii



it can be a volatile measure. Therefore, the metric is best presented as a moving average over at least 3–years as presented in the table below for the mining industry (i.e. resources sector, excluding oil and gas production). The relative performance on the secondary metric, compared to other key commodity export nations has not been assessed yet. Such a comparison would reveal the trend in relative energy price competitiveness of Australian miners. 2009/10

2010/11

2011/12

2012/13

Average annual change

Primary metric: Real Revenue ($2010) / Primary energy (GJ)

255

286

292

299

4.06%

Secondary metric: Nominal Revenue $ / Nominal $ energy spend

19

20

20

Energy productivity trends

1.72%

In order to double energy productivity from a 2010 base year, the industry would need to broadly maintain the current pace of improvement in energy productivity (i.e. 4% vis-à-vis a target of 3.5 % per annum. This is a significant challenge given that the improvement over the last four years was recorded at a time of historically high commodity prices and direct federal government policy support for energy efficient investments. Maintaining energy productivity at current levels may be challenging in itself, given the decline in ore grade and the forecast weakness in global commodity prices (Minerals Council of Australia, 2014a). It is envisaged that an appropriate voluntary 2030 energy productivity target will be established for the mining sector, by the sector. A2SE will consult with a diverse range of stakeholders about what this target should be. The determination of optimal pathways to achieve the target could be different for sub-sectors or groups within the sector. Views of the industry will also be sought about the best approach for tracking progress towards such a voluntary target, as well as what collaborative action the industry could take to support a significant improvement in energy productivity including with regard to action by government to reduce or remove barriers to achieving such a target.

Potential strategies for improving energy productivity.

Since energy productivity is a ratio of economic output per unit of energy (primary energy or cost as illustrated in the table below), the potential to achieve a voluntary energy productivity target could be influenced by adopting complementary strategies that: 

increase economic output; and/or



reduce the relative demand for energy.

Energy ‘productivity’ is not simply energy ‘efficiency’ by a different name. Energy efficiency, which generally focuses on using less energy to deliver the same output, is, however, an important element of one of the four key strategies, as illustrated below.

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Factors directly impacting energy input

Output dimensions ($ or other perceived value)

Energy Productivity Growth

The key strategies to enhance energy productivity are summarised below:

Opportunities to improve energy productivity in the mining industry



‘Traditional’ energy management – e.g. improving energy efficiency through better management of energy use including the implementation of innovative energy-use technologies, electrification, on site renewable energy and demand-management programs, as well as best practice in data management and benchmarking energy management to facilitate decision making with regard to energy productivity.



Systems optimisation – e.g. focusing on energy aspects of the mining and downstream minerals processing sector, such as the re-engineering of materials handling and mining processes, as well as industry supplychain capacity-optimisation strategies. These changes may be implemented for reasons of broader productivity improvement, but greater value can be realised by bringing a deliberate energy competency and focus to them.



Business model transformation – e.g. focussing on the energy aspects of fundamental longer-term change in the business of mining – relating to the design, development and operation of mining, as well as trading and asset management.



Value creation or preservation – e.g. focussing on increased throughput, beneficiation, and/or improving quality of ore shipped to smelters to reduce downstream energy consumption and air pollution associated with removing impurities during smelting (Pearse, 2014).

Australia is a global leader in mining-technology innovation and the sector has already made significant investments in improving the productive use of energy, as reported under the Energy Efficiency Opportunity (EEO) program. In spite of significant investment in energy efficiency, many unexploited energy productivity opportunities remain across the mining value chain, in mining, materials movement, comminution (intelligent blasting, mine-to-mill), ore sorting, classification or pre-concentration, reprocessing and product recovery. Industry best practice and many of the innovative new technologies that could transform the energy productivity of the sector have not yet been broadly adopted (Department of Industry 2012; Napier-Munn, Drinkwater, & Ballantyne, 2012). The Coalition for Eco Efficient Comminution (CEEC) estimates that a 15% improvement in energy productivity is possible by adopting best-practice v



energy management in comminution without investing in new equipment. Furthermore, investing only in new comminution technologies could deliver a further 10% to 30% reduction in energy used in this process, accounting for approximately 36% of total mine site energy (Ballantyne & Powell, 2014b; Brent et al., 2013). There are also significant enabling technologies to assist improving the energy productivity of materials movement/handling and minerals separation (Department of Industry, 2012). Mining companies are also investing in new forms of on-site energy generation, including diesel/solar hybrid systems (Vorrath, 2014). Investment by underground mines in energy efficient ventilation systems also has occupational health and safety benefits by reducing diesel fumes inhaled by miners. The optimisation of production processes by adopting lean manufacturing principles, as well as the evolution of new business models based on autonomous mining, truckless mines and the use of ‘big data’ across the whole value chain from exploration to processing also holds promise for supporting significant energy productivity improvement in the sector. However, the extent to which the Australian mining industry considers energy as part of the evolving operating and business models is not evident. Given the energy intensity of many mining processes and lessons from other sectors, ensuring energy is a central tenet in the design and operation of these new models will have a major influence on their success and the sustainability benefits. On-site renewable energy solutions could in certain cases help improve energy productivity by 2030. The intent is to explore the role of on-site renewables in the 2xEP Roadmap in a separate cross sector report.

Benefits from 2xEP for mining

As price takers, with very limited value added or product differentiation by producers, miners have two key strategies for optimising operating income: minimising costs and maximising throughput. Energy is already a significant cost to many mining companies. However, the convergence of declining ore grade, falling international commodity prices and declining profit margins across many Australian mining sectors since 2012–13 (ABS, 2014d) makes energy an increasingly important cost to be managed in the industry. The benefits of a significant improvement in mining energy productivity will depend on the voluntary target and actions agreed by the industry, but could include:

Mining program objectives



Energy efficiency improvements and cost savings for mining companies. These will significantly improve profitability and also reduce emissions.



Improved capacity utilisation and throughput.



Multiple dividends in terms of reduced maintenance and labour costs/unit of output, with a likely multiplier of up to 2.5 times the benefits directly attributed to energy savings.

A successful outcome from an A2SE 2xEP Roadmap process will be a realistic, but challenging, energy productivity target and plan developed by the industry, with the support of a broad spectrum of industry representatives to lead changes in the sector and their individual businesses to achieve the target. It is envisaged that an A2SE 2xEP roadmap will comprise:

vi


CONSULTATION DRAFT VERSION 1.3 

Definition of pathways to significantly enhance energy productivity, with reference to the different subsectors and scale of operations.



Identification of opportunities to collaborate to enhance Australia’s leadership position in mining and mining services.



Mechanisms to create greater awareness and adoption of emerging R&D innovations that can help mining sub-sectors achieve a step change in energy efficiency.



Strategies to overcome barriers to adoption of new, more efficient processing technologies



The initiation of new, or the strengthening of existing, programs to support businesses to achieve 2xEP.



Recommendations adopted by federal and state governments to enact policy changes to facilitate these activities and support 2xEP in mining.

These outcomes could be achieved through a collaborative process, involving miners, researchers and industry associations, with government engagement to accelerate innovation, transformation and value adding in the sector.

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Table of contents

1.

Introduction ................................................................................................................................. 1

1.1. Limits of this report ....................................................................................................................... 1 1.2. Structure of this report .................................................................................................................. 2 2.

The case for 2xEP in the Australian mining sector ................................................................. 3

2.1. Significance of the sector in the Australian economy and energy market.................................... 3 2.1.1. Impact on GDP and employment ........................................................................................ 3 2.1.2. Energy spend in the mining industry ................................................................................... 4 2.2. Australia’s international economic and energy competitiveness .................................................. 5 2.3. Linking economic productivity of the mining sector with energy use............................................ 7 2.4. Prevailing market conditions for key commodity sectors............................................................ 10 3.

Energy productivity in the context of the mining sector ...................................................... 15

3.1. Defining energy productivity ....................................................................................................... 16 3.2. Measuring energy productivity improvements in the mining sector ........................................... 18 3.2.1. Proxy for gross output at sector level and choice of energy metric................................... 18 3.2.2. Short term volatility in the value of output ......................................................................... 19 3.2.3. Conceptual integrated measurement framework for consideration................................... 19 3.3. What does a doubling of Australia’s energy productivity mean for the mining sector? .............. 20 4.

Potential for energy productivity improvements ................................................................... 23

4.1. Status quo?................................................................................................................................. 24 4.2. Application of energy in the mining sector .................................................................................. 25 4.3. Strategy area 1: Traditional energy management ...................................................................... 26 4.3.1. Ore characterisation and feed preparation ........................................................................ 26 4.3.2. Comminution processes .................................................................................................... 27 4.3.3. Froth floatation/ minerals separation ................................................................................. 27 4.3.4. Hauling/materials movement ............................................................................................. 29 4.3.5. Ventilation .......................................................................................................................... 31 4.3.6. Fuel switching .................................................................................................................... 31 4.3.7. Data and management practices....................................................................................... 32 4.4. Strategy area 2: System optimisation ......................................................................................... 32 4.4.1. Mine site ............................................................................................................................ 33 4.4.2. Beyond the mine site ......................................................................................................... 35 4.5. Strategy area 3: Business model transformation ....................................................................... 36 4.5.1. Autonomous mining ........................................................................................................... 36

viii



4.5.2. Truckless mines ................................................................................................................. 37 4.5.3. Real-time ‘big data’ transformation .................................................................................... 38 4.6. Strategy area 4: Preserve/increased output and quality ............................................................ 39 5.

Barriers to energy productivity................................................................................................ 41

5.1. Energy is not a ‘big enough’ issue .............................................................................................. 41 5.2. Short payback threshold for investments ................................................................................... 42 5.3. Management practices and cultural barriers .............................................................................. 42 5.4. Split incentives for energy efficient site development and operations ........................................ 43 5.5. Information, knowledge and expertise ........................................................................................ 43 6.

Overcoming the barriers .......................................................................................................... 45

6.1. Collaborative innovation ............................................................................................................. 45 6.2. People and organisational capabilities ....................................................................................... 46 6.3. Investment in energy programs .................................................................................................. 47 6.4. Incentives .................................................................................................................................... 47 6.5. Regulation and standards ........................................................................................................... 48 6.6. Other considerations................................................................................................................... 49 6.6.1. Address energy competitiveness issues arising from escalating energy prices ............... 49 6.6.2. Role of co-generation and renewable energy ................................................................... 49 7.

Next steps .................................................................................................................................. 50

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List of figures Figure 1: Mining energy spend by fuel type ............................................................................................ 4 Figure 2: Energy productivity of selected G20 countries......................................................................... 6 Figure 3: Mineral exploration activity in Australia .................................................................................... 8 Figure 4: Correlation between energy productivity and ore grade .......................................................... 9 Figure 5: Energy as a percentage of operating cost (based on estimates by Energetics) ................... 10 Figure 6: Profit margins declining across key mining sub-sectors ........................................................ 10 Figure 7: Thermal coal production cost curve – marginal mines at different price points (US$) .......... 11 Figure 8: Gold producers’ all-in sustaining cost is well below the current gold price (A$) .................... 11 Figure 9: Iron ore production cost curve................................................................................................ 12 Figure 10: Key determinants of energy productivity .............................................................................. 16 Figure 11: Conceptual overview of integrated measurement framework – applied to mining .............. 20 Figure 12: High level mining sector opportunity framework .................................................................. 23 Figure 13: Energy consumption by end use area at the mine site (energy units) ................................. 25 Figure 14: PwC MEPI – Open-pit loader and truck performance index (2003 = 1) .............................. 30 Figure 15: Where in the value chain will innovation create the greatest value over the next 10 to 20 years? .................................................................................................................................................... 36 Figure 16: Headline results from the 2013 Mining Innovation State of Play survey.............................. 42 Figure 17: Decline in the mining sector MFP ........................................................................................ 63 Figure 18: Increase in real cost per metre drilled .................................................................................. 65 Figure 19: RBA weighted commodity price index for base and bulk commodities ............................... 66 Figure 20: Increase in Australian resources and export volumes ......................................................... 67

x



Note: All dollars ($) are Australian dollars unless otherwise stated

xi



1.

Introduction Every one percent improvement in mining productivity translates to a $170 million saving for the Australian mining industry Andrew MacKenzie, CEO of BHP Billiton, cited in Vella 2013

This report provides a preliminary compilation of industry thought, leadership and analysis to support engagement with the mining sector in the Alliance to Save Energy (A2SE) Doubling Energy Productivity (2xEP) Roadmap program. It presents the rationale for action and summarises issues, opportunities and barriers. It considers the potential for industry-led energy productivity improvement initiatives in the mining sector. Using this report as a starting point, it is envisaged that the project will build on existing expertise and initiatives in the sector to develop a mining sector Roadmap, guide in-depth analysis of opportunities and challenges and develop policy responses. A2SE will canvass voluntary energy productivity targets that are realistic though challenging and related performance metrics. The A2SE project team will provide coordination and support.

1.1.

Limits of this report

Some energy productivity issues are common across the resources sector.2 However, this initial report excludes the oil and gas sub-sectors, principally because: 

The industry associations are generally different, with some exceptions, and may have developed different approaches to energy policy issues.



The energy challenges and commercial rationale for action on energy productivity are quite different. The oil and gas industry ‘self-generates’ and therefore does not pay directly for most of the operational energy consumed. The mining industry pays directly for the energy it consumes.



Opportunities for process-related improvements are different.

A2SE recognises the diverse nature of processes across the mining sub-sectors, and even between mines of the same commodities. It is difficult to generalise the opportunities. In this primer developed to support the start of a dialogue between a diverse group of stakeholders, we aimed to highlight a cross spectrum of opportunities. It is not intended as a comprehensive coverage of opportunities across the mining sub-sectors. Furthermore, the report does not address transport. This will be covered in a separate report dealing with freight transport across the economic sectors. The energy productivity of the metals smelting industry is included in the A2SE 2xEP Manufacturing Sector Overview. From a lifecycle perspective it is acknowledged that the mining industry can influence the energy intensity of downstream processing often beyond the Australian borders: Downstream metal recovery is absolutely dependent on the judicious expenditure of comminution energy which in turn depends on mining method (particularly blasting), but these three are not usually treated as an optimisable continuum in financial analyses Professor Tim Napier-Munn, founding Director, CEEC International Limited 2

Reference will be made to the oil and gas industry throughout the document as deemed appropriate, as well as indicating where data cannot readily be separated.

1



However, given the downstream efficiency gain can be tenfold (Pearse, 2014),3 both the mining and manufacturing sectors could consider how this cross-sectoral issue is best addressed within the 2xEP Roadmap program. Furthermore, the focus of the report is on electricity, diesel and gas consumed on mine sites and in transport from mines to ports. ‘Blast’ energy can have a significant impact on processing energy, and is discussed in this report. However, due to lack of data, we have not considered chemical energy contained in explosives as an ‘energy input’ in the calculation of energy productivity. Furthermore, whilst it is acknowledged that grinding media (e.g. forged steel balls) contains a great deal of embodied energy, this embodied energy is not a consideration within the scope of this report.

1.2.

Structure of this report

A background to the rationale for the doubling of energy productivity (2xEP) program is provided in Section 2, with specific reference to application in the mining sector. An overview of the contribution of the sector to the Australian economy, energy use and spend is provided, as well as the link between the productivity of the mining sector and energy use. This is framed in the context of Australia’s economic and energy competitiveness, as well as the prevailing market conditions for mining commodities. Section 3 provides an introduction to how the A2SE 2xEP initiative proposes to define and measure energy productivity, considerations for setting energy productivity improvement targets in the mining sector, as well as potential strategies for achieving significant energy productivity improvements. In Section 4 we discuss potential opportunities for improvement in each of the energy productivity strategy areas with specific reference to the mining sector. Barriers to energy productivity in the mining industry are discussed in Section 5, followed by an overview of potential policy responses and other actions that could address such barriers in Section 6. Potential next steps are presented in Section 7.

3

For example, low-grade concentrate shipped to China for smelting could result in significantly more energy being used to smelt out impurities, which could have been ground out locally with much less energy.

2



2.

The case for 2xEP in the Australian mining sector

The mining sector has a significant influence on the Australian economy in general and energy demand in particular. Attempts to address economic (including energy) productivity, without considering developments in the mining sector, would likely be ineffectual. In this context, economic and financial factors framing the energy productivity debate in the Australian mining sector are introduced using the following structure: 

Significance of the sector in the Australian economy and energy market



Australia’s international economic and energy competitiveness



Linking economic productivity of the Australian mining industry with energy use



Prevailing market conditions for key commodities

This section of the report provides the context for a discussion of the technical building blocks of energy productivity presented in Section 3.

2.1.

Significance of the sector in the Australian economy and energy market

According to a recent McKinsey study, mining is one of only four sectors4 in which Australia is deemed to possess existing strength and endowments to win in global markets (Lydon, Dyer & Bradley, 2014). The contribution of the sector to the Australian economy and energy use in the sector are briefly discussed below.

2.1.1.

Impact on GDP and employment

During 2013–14, mining contributed about 11% of Australia’s Gross Domestic Product (GDP), up from 7.8% over the preceding 10 years (BREE, 2014b). Mining support services and exploration contributed a further 1% (ABS, 2014b). Furthermore, the mining sector employed 2.3% of the total Australian workforce, whilst mineral exports contributed around 61% of Australia’s exports (BREE, 2014b). Australia is consistently ranked amongst the top five mineral producers in the world for bauxite, alumina, rutile, and zircon, as well as gold, iron ore, lead, zinc, lithium, manganese ore, uranium, nickel, brown coal, industrial diamond and silver (Australian Government, 2012), but much of the production growth over the last decade can be attributed to iron ore and liquefied natural gas (LNG). In 2012–13 iron ore accounted for 46% of the mining sector’s Gross Value Added (GVA) of $114.4 billion. Coal and the oil and gas subsectors each account for approximately 20%, with the remaining attributed to other mining (ABS, 2014a, 2014d). The mining equipment technology and services (METS) sector is valued at about $90 billion (Austmine, 2013). Although the contribution of the mining industry to the Australian economy varies from year to year as commodity prices fluctuate in response to global demand and supply, the impact of developments in the mining sector on the whole of the Australian economy is well illustrated by a 2014 Reserve Bank of Australia (RBA) study that estimates the mining boom:

4

The other sectors are agriculture, tourism and education

3



Raised the Australian real per capita household disposable income by 13%



Raised the average real wages by 6%



Lowered the national unemployment rate by about 1.25%

On the downside, the same RBA study estimates that manufacturing output in 2013 was 5% lower than it would have been without the mining boom, as a result of the impact of the strong Australian dollar. However, the de-industrialisation effect had been somewhat muted as some manufacturing sub-sectors benefitted from higher demand for inputs to mining (Downes, Hanslow, & Tulip, 2014).

2.1.2.

Energy spend in the mining industry

Mining, excluding extractive industries, accounted for approximately 13% of energy consumed in Australia in 2011–12 (517 PJ), excluding the transportation of products from mine sites (ABS, 2013b; Stadler 2015). This is likely to have increased in the last two years as the sector recorded strong output growth over this period, whilst demand for electricity from the economy as a whole has declined (Australian Energy Market Operator, 2014). As illustrated in Figure 1, liquid fuels (mainly diesel) represented 59% of the industry’s energy bill of $9311 million in 2011–12 (equivalent to 8% of total end-use energy cost to the Australian economy). This is not surprising as the Western Australian mines are generally off grid, generating their own electricity from diesel. Electricity is the second largest energy cost to the mining industry, accounting for 28% of energy use per annum (ABS, 2013b). Figure 1: Mining energy spend by fuel type

Electricity, $ 2623 mil, 28%

Liquid fuel, $ 5485 mil, 59%

Other, $ 378 mil, 4%

Natural Gas, $ 825 mil, 9%

The mining sector is, therefore, particularly sensitive to diesel price movements and a potential disruption to supply. With 91% of crude oil and refined fuels imported, Australian diesel prices (tracked by the global Singapore diesel price) are influenced by the Australian dollar exchange rate, as well as the level of government excise (and excise exemption). It is predicted that Australia will have no refining capacity by 2030 (Blackburn, 2014). Disruption of supply routes due to natural disasters, regional conflict or other factors will become an important business risk to be managed by miners as Australia’s in-country stockholdings of crude oil and refined fuels are as low as 23–30 days (Australian Institute of Petroleum, 2013).

4



Box 1: Fuel taxation in the mining sector As most diesel in mining applications is for off-road use the mining industry receives a Fuel Tax Credit of $0.38146 per litre. The rebate has been reviewed on several occasions, including in the run up to the 2014 Federal Budget. The Minerals Council of Australia advocates strongly for retention of the rebate on the basis that removal would lead to ‘double taxation’ (Deloitte Access Economics, 2014).

2.2.

Australia’s international economic and energy competitiveness

Productivity, in its most basic form, is the ratio of output produced to input used. Productivity is a key expression of the relative competitiveness of nations; competitive economies tend to grow faster over time and their populations tend to enjoy a higher standard of living. The productivity level ... determines the rates of return obtained by investments in an economy, which in turn are the fundamental drivers of its growth rates. (Schwab, Sala-i-Martin, & World Economic Forum, 2014)

Historically, productivity growth has been the dominant source of income growth in the Australian economy, with other sources of income growth being the terms of trade and labour utilisation. However, half the growth of Australia’s Gross National Income (GNI) over the period 2000–2012 is attributed to ‘one-off boom-time factors’ such as the favourable terms of trade during the extended mining boom5 (Gruen, 2012). This masked Australia’s virtually stagnant national multifactor productivity (MFP) 6 index over in the period 1995–2013 (ABS, 2013c). The competitive challenge for trade exposed sectors was exacerbated by an exchange rate well above the historical average (Lydon, Dyer, & Bradley, 2014). The cycle is now turning, as prices for key Australian commodities decline from their earlier highs and labour participation rates are likely to remain flat due to an ageing population (Gruen, 2012). Therefore, the only option for improving national income is to improve MFP, namely capital, labour and intermediary inputs such as energy. Total energy spend by end use sectors7 of the Australian economy was $111 bn in 2011–12, equivalent to 8% of GDP (ABS, 2013a, 2013b; Stadler, 2015). Energy productivity (see Box 2 below) could therefore play a central role in a broad based national strategy to lift GNI.

Box 2: Measures of energy productivity Energy productivity, measured as real GDP per unit of primary energy input, is a complex measure that reflects efficiency gains, as well as the effect of shifts in the economic structure and increased economic output. The relative cost per unit of energy inputs adds a further ‘competitiveness’ dimension to energy productivity, which reflects the relative cost competitiveness of countries in the use of their energy.

Australia’s energy productivity, measured as GDP per unit of primary energy input, is 14% lower than the average of the G20 countries in US$ purchasing power parity terms as illustrated in Figure 2. Over the period 1995–2012, Australia improved its energy productivity by a relatively low 1.1% per 5

Ratio between the prices of Australia’s exports and the prices of its imports.

6

This refers to capital, labour and other resource inputs

7

Excludes the cost of energy to the electricity, gas and petroleum refineries subsectors.

5



annum (World Bank, n.d.). The latter part of this period coincided with significant policy support for energy productivity investment which resulted in improved energy productivity for some sectors (ClimateWorks, 2013). However, many of the Federal Government programs aimed at stimulating energy efficiency investments have now concluded, including the Clean Energy Technology Investment Program (CTIP) and the Energy Efficiency opportunity program.

4%

12 3% $8.40

10 8

$7.20

GDP per unit of primary energy use (constant 2011 PPP $ per kg of oil equivalent)

14

2%

6

1.1%

1%

4 0% 2 0

-1%

Latest available

Average annual growth in energy productivity 1995 – 2012

Figure 2: Energy productivity of selected G20 countries8

Average annual growth rate

Not only are G20 countries, on aggregate, adding more economic value per unit of energy consumed, they are also improving faster than Australia, whilst leaders such as the European Union and USA have also set aggressive improvement targets: 

The European Union targets a 20% reduction in energy intensity9 by 2020 compared to 1990 levels and is now considering an extension of that target to 30% by 2030 (European Commission, 2013).



The USA has adopted a target to double energy productivity by 2030 compared to 2010 levels (The White House, 2013).



China, although currently lagging Australia on energy productivity, improved its energy productivity by 153% between 1990 and 2009. China is targeting a further improvement in energy productivity of 16% between 2011 and 2015 (Institute of Industrial Productivity, 2011; World Bank, n.d.).

In short, G20 peers are accelerating away from Australia at a time when domestic energy prices are increasing rapidly and prices in Europe and the USA are steady or declining in real terms (Stadler, Jutsen, Pears & Smith, 2014). Consequently, the potential contribution of energy productivity improvement to Australia’s overall economic productivity is now at an historic high. The country is 8

Latest available data for all countries was 2011 or 2012.

9

This is the inverse of the energy productivity measure.

6



coming from a low base, coupled with relatively high real energy prices. This means that in future the use of energy as a production input will have a more material impact on the profitability of mining companies and Australia’s economic growth compared with recent years.

2.3.

Linking economic productivity of the mining sector with energy use

The decline in overall productivity of the mining sector over nearly two decades is well documented. A brief discussion of drivers is presented below with more detail provided as Appendix D. Compared to the 1990s, the mining industry now achieves 56% less output per hour worked by employees and 44% less output in terms of capital employed (ABS estimate, cited in PwC, 2014a). However, a Bureau of Resources and Energy Economics (BREE) decomposition analysis of the reduction or erosion in mining sector productivity shed light on the impact of key factors influencing economic productivity as measured by the Australian Bureau of Statistics (ABS): For Australian mining as a whole, after removing the influence of both output quality depletion and production lags, multifactor productivity grew at an average annual rate of 2.5 per cent between 1985–86 and 2009–10. (BREE, 2013)

The decline in mining sector MFP should therefore be understood in the context of the convergence of the following factors during the mining boom: 

Bulk commodity and base metal prices were at long-term historical highs between 2006 and 2011, as illustrated in Figure 19 in Appendix D (RBA, 2014a). Because they are price takers, this was an opportune time for miners to maximise throughput, with a lesser focus on cost management.



A peak investment phase10 that has lasted at least five years (BREE, 2014b).



Continued decline in ore grade (metal extracted per tonne of ore.)

It is generally accepted that the high commodity prices and capital investment cycles have peaked (BREE, 2014b; RBA, 2014a). Prices have declined sharply, with gold experiencing a 27% drop, the largest in 30 years (KordaMentha, 2013; PwC, 2014b) and coal at a five year low (Paton & Riseborough, 2014). Furthermore, nearly half of the over $400 billion11 of resources, energy and related infrastructure projects undertaken in Australia over the last decade are now operational. Approximately $220 billion of projects are still under development (BREE, 2014b). As the industry enters a new cycle characterised by lower commodity prices and higher output as new capacity comes online, one of the three factors listed above, deteriorating ore grade, is likely to persist: 

The historical trend in the average ore grade for copper, gold, lead, zinc, uranium, nickel and silver is down (Mudd 2009, as cited in Fisher & Schnittger, 2012). Over the last 30 years, the average grade of mined Australian ore bodies halved, while the waste removed to access the minerals more than doubled. This has led to a 6% per annum increase in energy consumption across mining operations in recent years (Department of Industry, 2012).

10

Note that investment in energy-efficient capital equipment will be accounted for in the capital productivity component of the ABS MFP calculation.

11

Note this includes energy (i.e. oil and gas).

7





The number of ‘giant’ and ‘major’12 discoveries reported in Australia has declined since the 1990s (Productivity Commission, 2013).



The real cost of exploration per metre drilled has increased significantly since the 1990s, with a sharp drop in exploration activity evident since 2012, as illustrated in Figure 3 (ABS, 2014e, 2014f). A further 10% drop in exploration capital expenditure is predicted for the 2014 financial year (PwC, 2014b).

1,200

3,500

Brownfield ($ million) Greenfields ($ million) Total Metres Drilled ('000)

1,000

3,000

2,000 600 1,500 400

Metres drilled ('000)

2,500 800

1,000 200

500

0 Feb-2014

Apr-2013

Sep-2013

Jun-2012

Nov-2012

Jan-2012

Aug-2011

Oct-2010

Mar-2011

May-2010

Jul-2009

Dec-2009

Feb-2009

Apr-2008

Sep-2008

Jun-2007

Nov-2007

Jan-2007

Aug-2006

Oct-2005

Mar-2006

May-2005

Jul-2004

Dec-2004

Feb-2004

0 Sep-2003

Mineral exploration expenditure by type of deposit ($million)

Figure 3: Mineral exploration activity in Australia

Deterioration in ore grade has a direct impact on energy demand at mine sites (see shaded box below). The continued decline in ore grade, all else being equal, will place further downward pressure on the official MFP index for the mining sector.

12

‘Major’ is defined as greater than: 1 million oz Au; 100kt Ni; 1 million tonnes Cu equivalent; or 25kt U3O8 (Productivity Commission, 2013).

8



Box 3: Declining ore grade and energy use Ore grade drives key production metrics such as tonnes of material moved (TMM) as a ratio of saleable ore tonnes (TMM/t). However, declining ore grade does not only mean breaking and moving more rock to get the same output. It is also often associated with: 

Increased mine depth and overburden ratio (waste material to ore or coal production).



Moving rock over greater distances to reach processing facilities on the mine site.



More remote sites, which imply increased costs in providing energy for processing, coupled with additional investment in transport infrastructure to move production outputs from sites to the market as well as transporting labour and other production inputs to these sites.



Increased complexity of terrain/mine geology.



Reduced quality of ore (impurities, milling characteristics), which often demand more complex extraction methods.

Low-grade ores have a finer liberation size and, therefore, require finer grinding (using more energy) or alternative processing strategies. Simply put, when mining low-grade ore using current processing strategies, much more energy is consumed in breaking, sorting, processing and moving rock before saleable ore leaves the mine gate and then in transporting it from the mine to markets. These processing strategies were designed for high-grade ores, not low-grade ores, but the industry seems reluctant to adopt new approaches. The correlation between energy productivity and ore yield, of which grade is one of the key determinants, is well illustrated by the figure below, reproduced from the Co-operative Research Centre for Optimising Resource Extraction (CRC ORE) and Julius Kruttschnitt Mineral Research Centre (JKMRC) presentation (Ballantyne & Powell, 2014a.). Figure 4: Correlation between energy productivity and ore grade

140 130

Energy productivity

120

Index

110 100 90

Yield (grade)

80 70 60 50 1985

1990

1995

2000

2005

2010

As price takers, with very limited value added or product differentiation by producers, miners have two key strategies for optimising operating income (and GVA13): minimising costs and maximising throughput. Energy is already a significant cost to many mining companies, as illustrated in Figure 5.

13

Notwithstanding that GVA is statistically a different concept from operating income.

9



However, the convergence of declining ore grade and the prevailing market conditions, as discussed below, will make energy an increasingly important cost to be managed. Figure 5: Energy as a percentage of operating cost (based on estimates by Energetics)

20% 15% 10% 5% 0% Coal (open cut vs underground)

2.4.

Ferrous metals

Bauxite (Max: Alumina) From To Max

Gold

Non‐ferrous (Oxides/Sulphides)

Prevailing market conditions for key commodity sectors

The commodity price boom has also supported an increase in the average profit margin of miners from 10% in 2001–02 to 43% in 20011–12. Mining companies increased their capital investment over this same period rising from 14% of operating cost to an aggregate sector Capex:Opex ratio of 40%. Since then falling international commodity prices combined with high costs and distance from markets have put pressure on the profit margins of most Australian mining sub-sectors since 2012–13, as illustrated in Figure 6. This has also resulted in a sharp drop in the Capex:Opex ratio of the sector (ABS, 2014a, 2014d, 2014g; RBA, 2014a). Since 2011–12, falling international commodity prices combined with high cost and distance from markets to put further pressure on the profit margins of most Australian mining sub-sectors, as illustrated in Figure 6 (ABS, 2014d). Figure 6: Profit margins declining across key mining sub-sectors

Aggregate operating profit margin for mining sub‐sectors

40% 30%

2011–12

31% 29%

2012–13

25% 19%

18%

20% 10%

4%

14% 3%

0%

0% ‐10% ‐20% ‐21%

‐30%

‐22%

‐40% Iron ore

Coal

Copper Ore

Gold ore

Silver‐lead‐zinc ore

‐35% Bauxite & nickel

10



The HSBC Global mining index shed 46% of its value from 2011 to 2013, before showing signs of stabilising performance from mid-2013, with share price movements trending in line with the broader market (PwC, 2013b). However, temporary shut-downs in response to a global over-supply and falling prices are not uncommon and suggest that this is unlikely to be a broad-based trend (Paton & Riseborough, 2014). The prevailing market conditions amplify the intrinsic challenge faced by the resources industry, i.e. making long-term capital commitments when medium term revenue projections are volatile at best. Currently long range price projections suggest that prices will remain subdued for some time as illustrated in Figure 7 14 with reference to thermal coal below. Unless Australian coal sites in the third and fourth quartile move down the production cost curve, the negative impact on the Australian economy, rural communities and investors could be significant (RBA, 2014b; Kannan, 2015). Figure 7: Thermal coal production cost curve – marginal mines at different price points (US$)

The extent of the pressure obviously varies across the mining industry. With the current gold price above $1,400 / oz (Gold Price, 2015), most Australian gold producers would be viable with an average C1 cash cost of roughly A$860/oz (Létourneau,2014) and all-sustaining cost below $1,100 (See Figure 8 reproduced from Goldcorp, 2014). Figure 8: Gold producers’ all-in sustaining cost is well below the current gold price (A$)

14

Cost curves, reproduced from the RBA, August 2014 Statement on Monetary Policy (RBA, 2014b), based on average variable costs of production of mines

11



However, as illustrated in Figure 915 many Australian iron ore producers will be concerned at the current price level of approximately $60 / tonne. Figure 9: Iron ore production cost curve

A lower Australian dollar will not be a major factor in improving the performance of Australian producers, as US dollar strength also impacts the currencies of other major producers. Given that diesel is a major cost to many mines, the drop in oil prices could improve the performance of sites, but on a per tonne basis the impact on coal (for example) is only expected to translate to a $US1.80 per tonne drop in costs (Macdonald-Smith, 2015). In some regards, the drop in oil prices could make Australian producers less competitive on a CFR-basis (i.e. cost inclusive of freight), pushing them higher up the cost curve. As highlighted in a 2015 Bloomberg report, the drop in bunker fuel prices wiped out the price advantage of leading Australian iron ore producers over Brazil’s Vale SA, which could land a tonne of iron ore cheaper than its Australian rivals in China (Riseborough & Spinetto, 2015). Energy cost can therefore be a determinant of the relative competiveness of Australia’s resource sector on the global stage, especially at a time when global demand is weakening. As commodity prices decline and move ever closer to the ‘break-even point’ for many sites, the miners’ focus has shifted from being totally output-focused to recognising the need to balance volume growth and operating cost. Cost drivers are diverse, but relatively high labour costs, declining ore grade (which also drives increased energy use) and energy price escalations (see shaded Box 4 below), are all putting pressure on the operating profit margins of many mining sub-sectors and individual mines. Much of the initial productivity improvement programs are focused on cutting easily controllable costs (i.e. quick fixes), such as headcount reduction and negotiating price reductions from suppliers (KordaMentha, 2013; PwC, 2013b). This is not deemed to represent sustainable productivity gains.

15

ibid

12



Box 4: Energy prices The key energy cost driver for mines is often diesel prices. Diesel at terminal gate prices (TGPs) increased by about 40% from 2004-05, before stabilising from 2011-12 due to the strong Australian dollar. Due to global market conditions, the price dropped sharply towards the end of 2014, before gradually increasing again during 2015 as illustrated below (Australian Institute of Petroleum, 2015). The upward trend is expected to continue, albeit gradually (EIA, 2015).

Western Australia gas prices increased rapidly over the last decade, before easing back in recent years. Now large users on the Australian east coast have to deal with the prospective doubling of natural gas prices through to 2017-18, in addition to a 40% increase in real electricity prices for industrial users since 2005. This is double the rate of increase experienced by European industrial electricity users (Stadler et al, 2014).

In order to improve the economic productivity of the sector, the cost management focus needs to move beyond quick-fix cuts to sustainable efficiency gains based on best practice, smart investments in operations and innovative management approaches. Assigning a greater priority to energy-related considerations in decision-making can have a significant impact on delivering worthwhile improvements in operating profit (see the shaded box below: ‘Another lens through which to view energy cost as the industry enters a new cycle?’)

13



Box 5: Another lens through which to view energy cost as the industry enters a new cycle? Traditionally the ‘importance’ of energy to the business is expressed, as in Figure 5, by stating energy cost as a percentage of operating cost. This approach does not take into account the operating margins of the business. It would be appropriate if energy was a fixed cost and the industry was not exposed to volatile commodity prices; but this is not the case. In spite of the significant initiatives already embarked upon to improve the use-efficiency of energy in the mining industry, there are many more opportunities (some of which we will refer to in subsequent sections). A quote from the CEO of AngloGold is increasingly relevant to the industry as a whole:

It is best to be prepared for a low gold price environment, so you are better positioned to tackle an upside in the gold price Srinivasan Venkatakrishnan, CEO AngloGold (Australian Mining, 2013) In order to illustrate this point, we made the following assumptions about an ‘average’ iron-ore mine in 2012–13, when the industry aggregate margin was 29% (see Figure 6), all else being equal: 

The TMM/t for this mine is 2.8 and remains constant over the next few years



The energy cost as a percentage of operating cost is 10% (see Figure 5)



Diesel prices increase by 10%, largely due to exchange-rate fluctuation



Commodity prices decline from a realised $/t ore of $110 in 2012–13 to $97 in 2013–14.

What happens – in one year – when an increase in energy prices converges with a decline in commodity prices under these assumptions? Key parameter

% change

2012–13

2013–14

Energy cost as a % of operating cost

1%

10%

11%

Cost of production per tonne (energy cost in brackets)

1%

$78 ($8)

$79 ($9)

Operating margin

-10%

29%

19%

Profit/tonne

-44%

$32

$18

2012–13

2013–14

$3/t

$5/t

A $1/tonne reduction in energy cost will be equivalent to: An increased sales price of iron ore per ton

This modest improvement in the energy performance of the mine under these reasonable assumptions will translate under the 2013–14 scenario to a 27% improvement in operating profit per tonne; from $18 to $23/tonne (or increasing the profit margin from 19% to 24%). Alternatively, this is equivalent to a reduction in 14 tonnes of ‘dirt moved’ (TMM) for every 100t of saleable ore produced. As the operating margins of the industry decline in line with a drop in commodity prices, the ‘sales equivalent’ value of a dollar of energy saved per tonne of ore produced will increase proportionally. Note: These calculations exclude energy project cost. However, many energy projects have a payback of between one and four years, whilst cash flow neutral financing options are available for many energy solutions.

14



3.

Energy productivity in the context of the mining sector

Reaching agreement on the voluntary targets and associated metrics is a significant aspect of the work to be undertaken by A2SE and stakeholders. This section introduces some of the technical building blocks for consideration by mining sector stakeholders to support a mining-sector energyproductivity Roadmap process. These concepts are discussed in more depth in the 2xEP Framing Paper. However, a principle to highlight at the outset is that the 2xEP Roadmap is not engaged in the pursuit of energy productivity instead of capital or labour productivity. Energy productivity is an integral part of economic productivity. This approach is detailed in the A2SE 2xEP Framing Paper. The rationale is summarised in the shaded box below.

Box 6: The multiple links between economic productivity and energy ... Energy productivity is an integral part of economic productivity, which is typically defined by the three elements of the productivity equation, namely capital, labour and intermediate inputs. Energy use in the production process is included in the ‘intermediate inputs’ element of the equation, but a focus on energy productivity also impacts capital, labour and the productive use of other intermediate inputs. 

Capital Productivity: Investment in energy-efficient equipment is embedded in capital input. In addition, consideration of energy productivity as a step in the design, financing and operation of infrastructure and productive assets can support the optimal allocation of capital and enhance the return on assets over the life of the mine.



Labour Productivity: Energy-related investments directly contribute to job creation (i.e. increased labour-participation rate) in the energy sector, but can also indirectly influence the output-per-unit of labour in all other sectors (e.g. smart ventilation in mines can save energy and improve the health of miners).



Intermediate Inputs: The effective use of energy can also influence the effective use of other production inputs and associated waste streams to be managed. It therefore acts as a multiplier, with an IEA Study estimating that for every dollar saved in energy cost 2.5 x savings are realised elsewhere in the value chain.

However, the relationship between the elements of economic productivity and energy is not linear. Improving energy productivity is as much about efficiencies (i.e. doing the same things better or more cost effectively) as it is about innovation (i.e. doing things differently to achieve a better or even new value added outcome) (Stadler et al, 2014).

This section introduces energy productivity, possible measures, challenges in applying these measures to the mining sector and what they may mean in the context of doubling energy productivity. This discussion is structured as below: 

Defining energy productivity in general



Measuring energy productivity improvements in the mining sector



Exploring what a doubling of Australia’s energy productivity means for the mining sector.

15



3.1.

Defining energy productivity

Energy ‘efficiency’ and energy ‘productivity’ are frequently, but erroneously, used interchangeably. It is therefore useful to start by defining energy efficiency. Energy efficiency is the ability to deliver the same level of service or output using less energy. Energy efficiency is generally measured as end use energy consumed (typically in GJ) per unit of output (typically tonnes). Energy productivity aims to capture ‘multiple dividends’ that accrue from investment in more efficient plant and equipment including reduced operating and maintenance costs, as well as reducing downtime. In some cases this also includes increased output or improved quality of output, but in all cases it considers the qualitative dimensions of the societal impacts of production, including the management of water, chemicals and waste. Energy productivity is a measure of the total economic value delivered from each unit of energy utilised. The equation used in the A2SE’s 2xEP Framing Paper to develop a preliminary estimate of the scale of the task involved in doubling Australia’s energy productivity by 2030 is presented below: Equation 1: Basic energy productivity measure

2010

$

Energy productivity is thus more than traditional energy management, including energy efficiency, although it is one of the strategies to be considered as part of the 2xEP Roadmap, as illustrated in Figure 10 below. Figure 10: Key determinants of energy productivity

Factors directly impacting energy input

Output dimensions ($ or other perceived value)

Energy Productivity Growth

While it is understood that 2xEP may have a less direct influence on some elements included in the figure than others, it would nevertheless be valuable to bring a greater focus to the implications for energy productivity of initiatives targeting elements of both the input and output sides of the equation. The four energy productivity strategy areas are: 

Strategy area 1: ‘Traditional’ energy management – e.g. a focus on improving energy efficiency through better management of energy use, including the implementation of innovative energy-use technologies and demand-management programs, best practice in

16



data management, and benchmarking energy management to facilitate energy productivity decision making. 

Strategy area 2: Systems optimisation – e.g. a focus on the energy aspects of mining and minerals processing, such as the re-engineering of materials handling and mining processes, as well as industry supply-chain capacity-optimisation strategies. These changes may be implemented for reasons of broader productivity improvement, but greater value can be realised by bringing a deliberate energy-specific competency and focus to them.



Strategy area 3: Business model transformation – e.g. a focus on the energy aspects of fundamental longer term change in the business of mining – relating to the design, development and operation of mining, as well as trading and asset management. An example of a new operating model is the RioTinto Mine of the FutureTM, which changes the fundamental relationship between capital and labour inputs in the industry, with clear energy productivity benefits (see shaded box below).

Box 7:

’s Mine of the FutureTM

In operation since 2008, this initiative has enabled RioTinto to monitor operations in real time, improving unit cost and productivity through:  Contractor cost savings  Truck cycle time  Improved maintenance and life extension  Better performance of tyres  Reduced fuel consumption  Safety The concept being deployed at new Hope Downs 4 with expected planned total material movement with three fewer trucks, yields a 14% improvement over business as usual (Australian Bulk Handling Review, 2013);(RioTinto, 2013). RioTinto is reported to have saved over $80 million through tracking data from both their processing plants and trucks (Edwards, 2014). Picture reproduced from Rio Tinto, 2013



Strategy area 4: Value creation or preservation – e.g. a focus on increased throughput, beneficiation16 and/or improving the quality of ore shipped to smelters to reduce downstream energy consumption (by up to 10 times) and the air pollution associated with removing impurities during smelting (Pearse, 2014).

Consequently, energy productivity is not just about reducing inputs: it is also about increasing the value and quality of outputs. In some instances, this may lead to increased domestic energy consumption but improved energy productivity. 16

It is recognised that bulk commodities, by their very nature, are not focused on value-adding product features, though there are some exceptions. For example, the copper chain where ore is mined at 20%, upgraded to 80% in the minerals processing/ beneficiation stage and then refined to 99.99%.

17



3.2.

Measuring energy productivity improvements in the mining sector

Applying the macro-level energy productivity metric (Equation 1) to the mining sector presents a number of challenges. In particular: 

Gross output data is not available at sector level in Australia, necessitating the use of a proxy. Furthermore, primary energy as a denominator, though preferred as a national denominator (see A2SE 2xEP Framing Paper), is a less useful concept at the site level



Commodity price volatility can cause significant variability in the value of outputs (i.e. the numerator) over short periods of time



Geological factors (e.g. ore grade) can result in change over time in the ‘nature of the task’ required to deliver the same output (i.e. digging deeper, moving rock further. or grinding ore finer).

The effect of declining ore grade will be less sharply accentuated over a longer period of time. It has also been discussed in detail in Section 2.3. The following sections identify the key issues pertaining to the measurement of energy productivity due to the non-availability of gross sector output, choice of energy denominator and volatility in the value of outputs from the mining sector. This is followed by an introduction to the conceptual integrated measurement framework as a starting point for consultation with the mining industry stakeholders.

3.2.1.

Proxy for gross output at sector level and choice of energy metric

Gross Value Added is frequently used as a proxy for sector gross output. If this option is adopted, applying the common energy productivity metric (Equation 1) at the sector level could, therefore, be presented as illustrated in Equation 2 below: Equation 2: Sector-level energy productivity measure derived from Equation 1

$

However, GVA as a productivity numerator, by its very definition,17 excludes energy and other intermediate inputs that could contribute to a change in productivity. This presents a challenge for industries with vertically integrated supply chains, characterised by large inter-industry transfers (ABS, 2007). A recent European Commission paper also cautioned against the use of value added as an industrial output variable as it improperly implies that ‘efficiency-enhancing’ improvements in technology exclude intermediate inputs such as energy and other materials (European Commission Directorate-General for Economic and Financial Affairs, 2014). In order to overcome the weakness associated with using GVA, the dollar value of sales (i.e. value at factory gate) in real terms could be used as the numerator of a primary mining sector energy productivity indicator. Since energy costs are embedded in the ‘gross value of sales’ metrics, this overcomes the weakness associated with ‘value added’ as a numerator. This approach has been

17

Industry value added is equal to the total value of gross outputs at basic prices less the total intermediate consumption at purchasers' prices.

18



adopted by the American Alliance to Save Energy in measuring sector-level energy productivity performance. Primary energy could be replaced conceptually by delivered or final energy (see A2SE 2xEP Framing Paper) when cascading energy productivity to site level.

3.2.2.

Short term volatility in the value of output

The numerator, whether GVA or ‘gross value of sales’, can be very volatile (see the shaded box below), with prices for most minerals determined on international markets such as the London Metal Exchange. There are, of course, differences between the sub-sectors, with for example bulk commodities (i.e. coal and iron ore) trades typically based on long-term contracts and the diamond industry where De Beers exercise some control over supplies. Furthermore, the value of the dollar can fluctuate significantly over relatively short periods of time.

Box 8: Established and ‘new’ links between metals and financial markets adds to volatility of metals prices It is well recognised that the gold price is driven by investment market sentiment, with prices typically moving counter cyclically (KordaMetha, 2013). Copper has now joined gold as a ‘financial currency’, according to Goldman Sachs/Bloomberg, quoted in the PwC Mines 2014 report. Apart from traditional consumption demand, copper has been stored in bulk and used as collateral for lenders in China. In early 2014, ‘cash for copper’, rather than industrial demand, was deemed to be the dominant market factor driving copper prices (PwC, 2014b).

In order to align the longer timeframes in which energy productivity manifests and to smooth out volatility in numerators, measurement regimes typically adopt rolling averages over a timeframe reflective of the industry dynamics.

3.2.3.

Conceptual integrated measurement framework for consideration

For the purpose of tracking energy productivity over time, it will be necessary to develop a framework that is flexible enough to accommodate the diverse issues impacting the sector, as well as to counterbalance what is, in the short term, a volatile metric (e.g. by adopting a three- or five-year moving average).18 It is envisaged that an integrated framework will ultimately guide the cascading of metrics from the consolidated (i.e. total sector) level down to the level of the individual mine site. To ensure the relevance of measures at the sector, sub-sector and individual mine levels, this flexibility, could be attained through the development of a ‘dashboard of metrics’ with three levels: 

Primary (Sector and Sub-sector measure as per Equation 3): This metric is intended to most closely align with a national measure of energy productivity used to set targets and compare relative energy productivity at an international level. Equation 3: Proposed primary sector level energy productivity measure

18

$

$

The A2SE Framing Paper (Stadler et al, 2014) discusses these issues more extensively.

19



Secondary (Sector and Sub-sector measure as per Equation 4): This is an indicator of energy price competitiveness – i.e. the value created for each dollar spent on energy – could assist in reflecting the relative importance of energy as the operating margin of miners fluctuates with the rise and fall of commodity prices. Also note that a further key difference between Equations 3 and 4 is that the denominator used below refers to delivered or final energy, whilst Equation 3 uses primary energy. Equation 4: Proposed secondary sector level energy productivity measure



$ $

Tertiary (flexible suite of measures applicable at sub-sector and mine-site level): A set of tertiary level index-based indicators can be developed. These measures are unit insensitive and can be particularly useful at mine site level (i.e. tonnes, dollars or any other output unit that is an appropriate measure of economic value added in a sub-sector). Nonetheless, in some cases, simpler energy efficiency metrics may suffice. For example, a composite yield and energy use (GJ) index may be a practical and sufficient operational indicator of energy productivity at some sites.

These indexes could be rolled up into a higher-level composite energy-productivity index for mining, which, in turn, could be incorporated in a national index. Appropriate methodologies will be developed as part of the A2SE 2xEP roadmap process. The proposed measurement framework at the sectoral level (e.g. mining) is illustrated below. Figure 11: Conceptual overview of integrated measurement framework – applied to mining

3.3.

What does a doubling of Australia’s energy productivity mean for the mining sector?

An empirical analysis of 28 OECD countries spanning 32 years provides statistical evidence19 of the relationship between energy efficiency and GDP. Studies from organisations as diverse as the World Bank, McKinsey Global Institute and the Alliance Commission on National Energy Efficiency Policy also analysed the relationship between economic growth and energy efficiency. Typically the potential beneficial impact on global GDP by 2030 of adopting energy-efficient practices is estimated at around 2%, with 3.2% being the upper range of forecasts (Stadler et al, 2014). This is a significant 19

The study found that there is a less than 1% chance that the statistical results have been obtained by chance.

20



contribution to GDP, given that the Group of 20 (G20) nations will aim to lift their collective GDP from all economic activity by more than 2% above the trajectory implied by current policies over the coming five years (G20, 2014). In Australia, the 2xEP program is proposing a doubling of energy productivity by 2030 as the target for the economy-wide program. This target is estimated to equate to an increase in GDP from $222/GJ to $444/GJ of final energy demand, based on preliminary analysis (Stadler, 2015). This reduction equates to a 3.5% per annum improvement in energy productivity across the economy. About 60% of this change is expected to come from structural changes in the economy, such as a decline in heavy manufacturing and an increase in ‘services’ and economic growth (i.e. an increase in output). The remainder – a 1.4% annual improvement across the economy – will need to come from energy-productivity improvements. This is well above the overall long-term historical trend (0.4% p.a. over the last two decades) (Stadler, et al 2014). As discussed later in this paper, energy-productivity investment incentives and associated policy settings have deteriorated in their ability to stimulate energy efficiency investments. For companies, an energy productivity target is in many regards ‘easier’ to achieve than an energy efficient equivalent, since some of the improvement is driven by increased production output. This is evident from the performance of the mining industry over the recent past as illustrated below (Stadler,2015). In this way the energy productivity metric ‘recognises’ the shareholder value imperative of growing outputs faster than inputs. Since the energy productivity metrics are sensitive to both commodity and energy prices, it can be a volatile measure. Therefore, the metric is best presented as a moving average over at least 3–years as presented in the table below for the mining industry (i.e. resources sector, excluding oil and gas production). The relative performance on the secondary metric, compared to other key commodity export nations has not been assessed yet. Such a comparison would reveal the trend in relative energy price competitiveness of Australian miners Table 1: Recent mining industry-level energy-productivity performance (3-year moving average) 2009/10

2010/11

2011/12

2012/13

Average annual change

Primary metric: Real Revenue ($2010) / Primary energy (GJ)

255

286

292

299

4.06%

Secondary metric: Nominal Revenue $ / Nominal $ energy spend

19

20

20

Energy productivity trends

1.72%

In order to double energy productivity from a 2010 base year, the industry would need to broadly maintain the current pace of improvement in energy productivity (i.e. 4% vis-à-vis a target of 3.5 % per annum). This is a significant challenge given that the improvement over the last four years was recorded at a time of historically high commodity prices and direct federal government policy support for energy efficient investments. Maintaining energy productivity at current levels may be challenging in itself, given the decline in ore grade and the forecast weakness in global commodity prices (Minerals Council of Australia, 2014a). Modelling at the sectoral level will seek to develop robust estimates of the potential contribution from the mining sector. Whatever the agreed target is, it will be industry-driven and voluntary. However, there are a wide range of opportunities available to miners, as discussed in Section 4, across all four strategic areas that could support a range of pathways to improved energy productivity for all types of mines.

21



Consultation notes ... Key points for consultation include: 

what a feasible target for the sector should be, considering that ore grade deterioration is likely to increase rather than decrease in the years to come.



how the target should be measured.

e.g. would a realistic target be to stabilise or flatten the current increasing levels of energy intensity by 2025-30 using the general metric used in other sectors, or can a ore-grade factor be included in the calculation of a measure? Are there other options?

22



4.

Potential for energy productivity improvements Please note ...

A2SE compiled a preliminary collection of practices that could provide a starting point for discussion with mining sector stakeholders on potential pathways to improving energy productivity. This is by no means intended as a complete or comprehensive list of opportunities in a diverse and dynamic sector.

This section provides an overview of the status quo, sketching, by reference to a few industry sources, the likely scope for improvement. It also provides a brief introduction to the application of energy in the sector as background to the discussion of opportunities. The section covers both established best practice and emerging opportunities that, if more broadly adopted, could have a material impact on energy productivity in the sector. These opportunities will be discussed within the four broad strategy areas supporting an energy-productivity agenda introduced in the previous section, namely: traditional energy management, system optimisation, business-model transformation and value creation/preservation as illustrated in Figure 12 below. Figure 12: High level mining sector opportunity framework

23



However, it should be noted that two themes run across all four strategy areas, namely innovation, be it technology, process or whole of business model, as well as data management, which is an increasingly central part of mining operations.

4.1.

Status quo?

The industry has already made significant investments in energy efficiency. For example, mining companies participating in the EEO Program identified 6 PJ in diesel savings (equivalent to 6% of total diesel consumption by mines). A total of 66% of these opportunities were adopted as early as 2008– 09 (Department of Industry, 2011). Furthermore, a 2013 evaluation of the EEO Program estimated that the mining industry saved 19.4 PJ during the first five-year cycle, of which 8.5 PJ were attributed to the impact of the EEO Program (ACIL Tasman, 2013). Historically, upsizing equipment and technology innovation have driven most of the improvement in mining operations. In the case of copper mines, technological innovation has been the key driver, as illustrated in the diagram from a 2010 MinEx Consulting study reproduced in the shaded box below (Schodde, 2010). Possible options to realise further reductions in energy costs through an integrated approach to energy productivity – covering technology, process, systems, and business models – will be discussed in subsequent sections.

Box 9: Impact of technological innovation A 2010 study by MinEx Consulting across a number of copper mines in Chile and the USA indicated that economies of scale contributed 30% to the reduction in $/ton ore between 1905 and 2007, with the remaining 70% attributed to cost savings from new technologies.

Reproduced from Schodde, 2010

In spite of significant investment in energy efficiency, many unexploited energy productivity opportunities remain across the mining value chain, in mining, comminution concentration and materials handling. According to CEEC, adopting best practice can deliver up to 15% improvement in comminution, without any equipment replacements. Furthermore, the energy efficiency of some key end-use applications has not yet been optimised. For example, with reference to comminution, crushers are estimated to be 75% energy efficient and a ball mill 3–15% efficient in producing the

24



same size distribution as single particle breakage with significant improvement potential of up to 30% identified (Tim Napier-Munn, 2014). With specific reference to comminution, a founding director of CEEC in the keynote address at Comminution 2014 highlighted that: There is a strong consensus in the literature and anecdotally amongst the experts that savings in the range 5–30% are attainable now by implementing what is already known, i.e. by adopting and sustaining best practice. This is not easy in an industry that has decimated its experience base in recent years but can and is being done. In the longer term (10–20 years), with investment in the new technologies discussed above and with the opportunity to build new energy-efficient plants in brown- and green-field developments, savings exceeding 50% are possible (Tim Napier-Munn, 2014)

4.2.

Application of energy in the mining sector

Very broadly, energy use at the mine sites is split 50:5020 between mining/materials handling and processing (i.e. ore concentration at the mine), with additional energy expended transporting production from the mine to markets. This is broadly in line with a study on energy use in mining conducted in 2007 by the U.S. Industrial Technologies Program (U.S. Department of Energy, 2007) to identify energy saving opportunities in underground coal, metals and mineral mining. The average energy consumed by area from that study is reproduced in Figure 13 below. Figure 13: Energy consumption by end use area at the mine site (energy units)

5%

4% 2% 2% 6% 7%

Blasting Dewatering Drilling 10%

Digging

Mining 27%

Ventilation Electric equipment 4%

42%

Diesel equipment Grinding Crushing Separation

Material Handling 22% Processing 51%

18%

Across all types of mines, the energy consumption associated with grinding far outweighs the energy consumption of other operations. Grinding consumes about 42% of energy use, while materials20

Rule of thumb provided by Energetics for Australian mining operations.

25



handling diesel equipment is the next largest energy consumer, accounting for 18%, or less than half of the energy required for grinding. The third largest energy consumer is ventilation, accounting for only 10% of total energy use. Although upstream energy consumption is relatively low, it should be noted, as discussed in the sections following, that actions taken earlier in the value chain (e.g. blasting) can have as much as a 40% impact on energy consumed downstream. The end-use break-up differs materially between open-cut and underground mines. Typically open-cut mines use diesel for the fleet, whereas underground mines use more electricity for ventilation and moving rock, as well as some diesel (for moving people). In off-grid mines, electricity is typically provided by diesel generation sets, so all the energy used is diesel. Each of the top three energy end use areas illustrated in Figure 13 is briefly discussed in more detail in Appendix C.

4.3.

Strategy area 1: Traditional energy management

The traditional energy management strategic area includes the use of energy-efficient equipment, electricity and gas demand management, energy data management and practices to embed energy efficiency into the corporate and site-management culture. Opportunities exist in a wide range of areas, but we will briefly discuss this strategic area in the following sub-categories: 

Ore characterisation and feed preparation



Comminution processes



Froth floatation / mineral separation



Hauling/materials movement



Ventilation



Fuel switching



Data and management practices

4.3.1.

Ore characterisation and feed preparation

Significant energy can be saved downstream by reducing the amount of rock moved for processing. Ore characterisation and feed preparation opportunities, where the impact of investment is primarily amplified in downstream processing benefits, will be discussed with system optimisation in Section 4.4. In this section, we highlight some of the opportunities that impact upstream energy productivity, namely: 

Improved characterisation of ore bodies by using 3D geometallurgical models to target the highest concentration ore bodies for blasting and extraction (Department of Industry, 2012)



Smarter blasting (discussed in more detail on page 33)



in-situ processing underground



Early gangue rejection strategies, such as coarse gravity separation, low-grade pebble rejection from SAG product, and pre-concentration by screening and ore sorting (Ballantyne, Hildren, & Powell, 2012)

26



Improving the efficiency of crushing and grinding ores by pre-concentration also reduces water requirements and, therefore, the pumping requirements (Smith, 2014a)



Feed-quality improvement using screening- and sensor-based techniques to sort and reject low-grade ore/waste at the earliest stage possible (Department of Industry, 2012), thus, eliminating the transport and handling from mine-to-mill.



Sorting at multiple points prior to grinding



Blending of ore and stockpile management to determine best feed blend, which can increase processing throughput.

4.3.2.

Comminution processes

Key areas for potential improvement include: 

Flow-sheet optimisation; modifying the existing circuit to push size reduction forward (i.e. crushing) so that less grinding is required (Buckingham et al., 2011)



Choosing the optimum target size(s) at each stage of the circuit through understanding liberation size; the target size could be increased, which means less material going to further size reduction (Pokrajcic, 2008)



Automation of circuit operation using expert control systems; this includes optimising the use of existing control systems with regular tuning and maintenance of the systems (Australian Government, 2010)



Using more efficient comminution equipment (e.g. more crushing, HPGR and IsaMIl); tumbling mills are generally the least-efficient comminution machines and should be phased out where possible (Napier-Munn, in press).



Improve the energy efficiency of motor systems. Electric motors are used to drive crushing and grinding mills. These consume a significant percentage of energy in comminution and hence improving their efficiency can make a significant difference (Ravani von Ow & Bomvisinho, 2010). For example, Barrick Gold Corporation achieved 4.4% energy efficiency improvements in their motor systems in their mills (Smith, 2014b)

4.3.3.

Froth floatation/ minerals separation

Electrical energy contributes significantly to the running costs of mineral separation through froth floatation. There are many energy efficiency opportunities to reduce these costs as illustrated in The relative performance on the secondary metric, compared to other key commodity export nations has not been assessed yet. Such a comparison would reveal the trend in relative energy price competitiveness of Australian miners Table 1 (reproduced from Murphy, 2013) Table 2: Energy saving opportunities in an existing flotation plant Process

Maintenance

Re-engineering

Feed size optimisation Pulp density optimisation Airflow rate optimisation

Correct drive train alignment Correct belt tensioning Maintaining lubrication schedule

Alternate flotation mechanisms Pipe re-routing Sump design 27



Process

Maintenance

Re-engineering

Impeller speed optimisation Revision of control philosophy

Wear component replacement

Re-size pumps Assess high efficiency motors Assess variable speed drives

Opportunities also exist to maximise a plant’s energy efficiency in the design phase. Design, layout and equipment selection should all be performed with the view to optimise the energy efficiency of the circuit. Key considerations in this regard, when selecting a new froth floatation separation plants are: 

Utilise maximum possible flotation particle size.



Maximise use of gravity flow of intermediate streams rather than pumping.



Evaluate the power use of process equipment such as flotation tanks and pumps on predicted energy consumption rather than installed motor power.



Ensure energy usage is included in the decision making process and is highlighted in the financial evaluation of different options.



Judiciously use safety factors in flowsheet design. Overdesign can lead to a less energy efficient process (Murphy, 2013).

28



Box 10: Emerging developments in froth floatation Currently, mineral ores are crushed and ground down to a size small enough to undergo froth floatation to separate out the valuable minerals from the mineral ore. Thus, there is an upper limit on the size of the particles that can be treated at present, so all the material to be floated must be ground to below this size. The top grinding size for flotation with current technology is typically 150 microns, not much bigger than a human hair. If the top size were raised to 600 microns, the grinding energy would be reduced by half. (Smith 2014b). This is because the amount of energy needed to grind particles into smaller and smaller pieces rises exponentially as illustrated in the diagram below, reproduced from the CEEC website (CEEC, 2012). So reducing the size required for froth floatation has significant energy efficiency implications Laureate Professor Graeme Jameson, based at Newcastle University, is developing a new flotation process – the Fluidised Bed Flotation Cell – especially for the flotation of coarse particles. He reasoned that the cause of the low recoveries achieved with coarse particles was the high degree of turbulence in conventional flotation cells. Instead of using a mechanical agitator, he found that if the particles were levitated with an upflow of water in a fluidised bed, he could provide a gentle environment for contacting bubbles and particles. Very high recoveries have been achieved with mineral particles up to at least 1.4mm in size – three times the size of an average grain of sand. This offers the potential to save energy in crushing and grinding by an order of magnitude. As well as saving energy, the fluidized bed cell has the potential for significant reductions in water use, because it can take feed slurries that are twice as dense as used in current practice. The new technology will soon be trialled on real ores at an operating concentrator (Smith 2014b). Further information about this new flotation process, currently in the R&D phase, please click here.

4.3.4.

Hauling/materials movement

There are many opportunities to improve the energy efficiency of materials at mine site and beyond. On-site energy-efficiency improvement opportunities can be broadly grouped into the following three areas: 

Improve haul truck fuel efficiency or use alternatives such as conveyer belts (i.e. electrification) or Rail-Veyor® systems21



Retrofit electric draglines to make them more energy efficient, or use overburden slushers (OS) instead of traditional electric draglines (Department of Industry, 2012, as cited in Smith, 2014a)



Loader efficiencies

21

The Rail-Veyor® systems combined the functionality of rail haulage, trucks and conveyor. More information is available at http://www.railveyor.com/about-rail-veyor-bulk-material-handling/

29



We will briefly discuss opportunities related to truck performance improvement in more detail given the cost associated from both a capital and diesel usage perspective. Furthermore, the recent PwC Mining Equipment Productivity Index (MEPI) suggests that the performance of trucks in particular has been declining since 2009. A graphic from the recent PwC Mine 2014 report is reproduced as Figure 14 to illustrate this point (PwC, 2014b). Figure 14: PwC MEPI – Open-pit loader and truck performance index (2003 = 1)

The efficiency of hauling processes is influenced by mine planning, production scheduling, pit design, dump design and the geography of sites (Department of Industry, 2011). The performance assessment by PwC illustrated above has a capacity and, therefore, capital utilisation dimension, but this will also flow through to operating dimensions impacting energy costs such as idle time, route optimisation and other related factors, as discussed below. The range of strategies to improve the performance of trucks includes: 

Light-weighting such as the use of aluminium truck beds in coal so that less energy is used moving the truck, thus investing the energy in moving coal



Route optimisation to minimise stoppage and gradient and maximise the duration of constant speed



Optimised driving practices, maintenance and management



Use of conveyor systems with easily replaceable parts ensures fuel is not wasted on moving the vehicle itself; parts can be replaced cheaply and quickly, and there is virtually no maintenance downtime

The use of data is central to most strategies. Sophisticated on-board data collection and real-time information display capabilities also enable the evaluation of haul road designs to maximise the duration of optimal truck speeds, as well as improve driving practices. This has been effectively illustrated by, for example, the Fortescue Metals Group, which identified 768kL in fuel savings associated with a single unnecessary stop per payload cycle across its fleet at the Cloudbreak and Christmas Creek sites (Department of Industry, 2011).

30



Consultation note ... In light of technological advances, is there scope to review the ‘rules of thumb’ used on the industry to trigger reviews to move from decline to shaft designs and / or trucks to conveyer belts? Is there scope for wide spread electrification using e.g. hybrid diesel-renewable energy solutions to assist marginal mines in moving down the production cost curve? What factors, other than high upfront capital cost (e.g. operational flexibility of trucks) is limiting the uptake? What options should be considered to de-risk such a major capital commitment in an industry characterised with volatile revenue streams? What is the scope for:

4.3.5.



innovative ownership models



government policies such as accelerated depreciation



other?

Ventilation

Underground mines can use 15–20 tonnes of air to produce 1 tonne of ore (Natural Resources Canada, 2013) making ventilation one of the biggest contributors to energy use. Ensuring that redundant workings are not ventilated and have been properly closed off can make for relatively easy savings. Recent innovations in ventilation include polymer ducts and improved controls to promote optimum ventilation. Rigid polymer ducting, which reduces air friction, is an energy-efficient alternative to large ducts made of fabric. Transport costs are also reduced, as the sheets are assembled at the mine (Mining Association of Canada, 2012). Optimum ventilation is important from both a labour productivity and energy-management perspective. Air quality, temperature and pressure (i.e. air conditions) are essential for maintaining a satisfactory work environment for miners. However, since 2012 there has been an increased obligation on the industry to mitigate health risks. This is a consequence of the World Health Organisation adding diesel particulate matter to its list of Grade 1 carcinogens, after concluding that long-term exposure to the fumes was a cause of lung cancer (International Agency for Research on Cancer, 2012). Consequently, although maintaining optimal air conditions is complex, it is essential from a productivity and safety risk-mitigation perspective. Advanced control systems are available that support more energy efficient ventilation, enabling the supply of air only when it is required and where it is needed and adapting the flow to the specific needs of those areas. Using thermodynamic modelling, these systems simulate airflow, including the movement of diesel particles, pressure and temperature (Mining Association of Canada, 2012). Innovative, cash-flow neutral financing solutions for advanced ventilation systems are also available in the Australian market.

4.3.6.

Fuel switching

Fuel switching could become an attractive alternative to diesel trucks and diesel electricity generation, especially given that nearly all liquid fuels are imported and the forecast is for the Australian dollar to continue its downward adjustment. A number of options that are increasingly gaining attention are: 

Diesel-solar hybrid generation sets that can provide cost-effective and reliable supplemental power in remote and regional areas (Vorrath, 2014)



Wind turbines, which can be financed though power purchase agreements 31



Electric powered underground vehicles (Mineweb, 2013) and LNG driven trucks – e.g. Shell Canada and Caterpillar signed an agreement in December 2013 to test a new engine and fuel mix using LNG, which could reduce greenhouse gas emissions and operating costs (PwC, 2014b)



Energy generation from waste coal seam gas (see shaded box below). Box 11: The Clean Energy Finance Corporation (CEFC) supports fuel switching initiatives in the mining sector

The CEFC is providing $75 million to Energy Developments Limited (EDL) for investment in new projects generating energy from waste coal mine gas and landfill gas as well as remote hybrid renewables projects (CEFC, 2013).

4.3.7.

Data and management practices

Best practice energy management is pervasive across all the areas discussed above, including data collection, monitoring and control. In this section, we highlight a few general areas of potential improvement, namely: 

Benchmarking,



Energy contract management; and



Procurement.

Achieving progress on energy efficiency is underpinned by corporate support, clear plans and the establishment of accountabilities and targets. Benchmarking is a key tool in establishing targets. Work done by the CRC ORE, Julius Kruttschnitt Mineral Research Centre (SMI JKMRC) and the University of Queensland in benchmarking comminution energy consumption is now providing a reliable and rich dataset to support mine specialists. Tools developed through this process can assist the industry in identifying inefficient parts of the comminution circuit, changes in grind size to improve efficiency, and ore upgrade strategies (Ballantyne & Powell, 2014). Energy contract management and associated demand-management strategies can deliver savings, in particular for mine sites using grid electricity. Many sites are not aware of the terms of the electricity contracts negotiated by the ‘corporate office’ e.g. they don’t realise the significance of peak demand (KW or KVA) charges for equipment of their size (drag lines, long walls, mills), and the fact that energy consumption (kWh) often makes up less than 50% of total electricity charges. The energy profile of many mines is determined by contract miners, rather than mine owners. Integrating energy considerations into the performance metrics of procurement contracts of contract miners is an essential part of any energy productivity strategy.

4.4.

Strategy area 2: System optimisation

Regardless of commodity prices or ore grades, mining companies need to design processing strategies that will withstand the cyclic nature of the industry. Whilst many energy-management actions in mines already adopt a ‘whole of system’ view of energy, operational silos and perceived competitive differentiation between miners in the same geographic area hinders progress.

32



In the following two sections, we will discuss tactics and strategies that can facilitate system optimisation at the mine level, as well as beyond the mine, upstream and downstream, across the value chain at industry level.

4.4.1.

Mine site

Systems optimisation, at site level, incorporates process control systems, which are widely used to monitor and control particular processes within a mine site, often enabled by advanced communication protocols, such as remote stations (sensors), automated or operator-driven commands are sent to remote station control devices (actuators) (Department of Energy, Resources and Tourism, 2010b). It requires management to take a broader view of the business, beyond their own operational silos, during both design and operation stages. Adopting a system-wide view of everything that happens on a mine site can unlock significant upstream and downstream benefits. We will discuss this with reference to opportunities and developments pertaining to: 

Smart blasting



Characterisation of ore and target mineral size



Optimal processing strategy



Whole of site operations

Smart blasting Modifying blasting practices to achieve a more suitable mill feed size can increase throughput, as well as reduce downstream energy demand, by as much as 30 to 40%. Chemical energy in explosives is the cheapest form of energy used in the mines. Whilst it has been recognised for some time that high impact blasting can reduce the need for downstream crushing and grinding, blast energy can cause fly rock, excessive vibration, air blast and wall damage. A team of researchers recently had a breakthrough in energy efficient blasting that could reduce the downstream energy demand by as much as 40% whilst avoiding the environmental and safety concerns associated with high intensity blasting (ORICA, n.d.). See shaded box below.

Box 12: Energy efficient blasting to reduce the downstream energy demand Dr Geoff Brent and his research team was recently awarded the CEEC Medal for ground-breaking research in ultra-high intensity blasting (x5 the standard practice) that has the potential to deliver a step change in mine process efficiency, increasing mill circuit throughput by up to 40% (ORICA, n.d.). Upstream energy consumption increases, but end-to-end there is a significant improvement in the use of energy in the process. This new blasting method, which overcomes past safety and environmental concerns, involves:

dual blast layers within a single blast event that is initiated with electronic blasting systems. An upper blast layer comprising conventional powder factors is initiated first and the broken rock is allowed to fall to rest before initiation of the lower layer which comprises ultra-high powder factors and hence considerably higher blast energy. The broken rock from the earlier-firing upper layer provides an effective buffer to avoid fly rock, enabling powder factors in the range 2–5 kg of explosives per cubic metre of rock to be achieved with control (CEEC, n.d.)

33



The next challenge is to determine how to recover the ore from rock without having to make the particles small enough so that the material presents on the surface to be dissolved. Gold recovery is still achieved using cyanide – a process discovered in the late 1800s in Scotland. Developments in the areas of heap leaching and in-situ leaching of rock are particularly encouraging for the gold-mining sector where one tonne of rock is currently moved to obtain 4–8 grams of gold (i.e. 4–8 parts per million).

Characterisation of ore and target mineral size Characterisation of feed ore based on variability ensures that performance is optimised for different feed characteristics. There are numerous research programs and market-ready offerings in this area, such as the CRC ORE Grade Engineering®. The reported production impact from Grade Engineering® includes a 5.7% improvement in throughput and 6.5% improvement in ore grade using 4.3% more energy (Scott, 2014). This occasions a net gain in energy productivity, despite increased energy use. The CSIRO also recently announced a new breakthrough using a magnetic resonance technique to develop a sorting sensor designed for use at mine sites and processing plants processing larger, lowgrade deposits at thousands of tonnes per hour (CSIRO, 2013). It is also important to target mineral ore product size, or grind size as it significantly affects the energy intensity of the comminution. The final grind size of mineral ore particle needed to be small enough to separate valuable mineral from ore bodies during froth flotation. Progressive mineral liberation is an alternative strategy for the selection of a target product size for multi-mineral ores is the progressive liberation strategy. This involves liberating one mineral or one group of minerals at a time (Department of Industry 2012).

Optimal processing strategy New deep-vein mining methods include in-situ or underground processing, which removes the need to transport large volumes of waste rock to processing sites. The CSIRO, in a joint venture with Glencore, has developed a sensor that gauges how well the mill is working by monitoring sound waves. Acoustic data analysis from sensors across mill chambers provides an indication of the distribution of steel balls in the mills that grind ore. According to Glencore’s head of mineral processing technology, Lindsay Clark: The ultimate plan for using this equipment is to reduce costs, reduce power consumption and to also reduce maintenance costs by having the media spread throughout the mill. (Chambers, 2014)

AngloGold Ashanti also achieved significant productivity gains, including in energy, by optimising the control of the crushing and milling circuit at their Australian mine. This was achieved by modifying the software logic and control algorithms, without the need for new hardware, enabling operators to proactively use the control system to keep the plant working within defined operational parameters (Clean Energy Ministerial, 2013).

Whole of site operations Application of new mining methods based on the latest advances in robotics, as well as real-time monitoring of the flow of rock and ore through the mine and processing plant, are no longer the exclusive domain of large miners. It is increasingly the way operations are conducted. 34



BHPBilliton and Rio Tinto have been applying Lean and Six Sigma practices for many years. More recently, this approach has been adopted by Anglo American, which reviewed and restructured 50% of its operations with a focus on executing planning and production in a similar way to a manufacturing company. Chief Executive Officer (CEO) Mark Cutifani is reported as saying that the ideal scenario for Anglo American would be similar to the Toyota operating model, such as lean manufacturing, Six Sigma and Integrated Asset Planning to transform its mines (Leonida, 2014). Previously Anglo worked with CRC ORE at its Mogalakwena platinum mine in South Africa to resource characterisation, smart blasting and ore sorting, to achieve a 2-2.5 fold increase in ore body concentration for the feed into “grinding” mills, leading to significant energy savings (CRC ORE, 2013, cited in Smith, 2014b). The mine also slashed waste generated by 50% from 200Mt/y to100Mt/y. Over the next 15 years, this is expected to save the company US$1.7 billion dollars. The new operating model for Anglo’s Moranbah coal mine in Australia, implemented with no extra capital, has seen a significant increase in production in 18 months from 3.5Mt/y in 2012 to 5.5Mt/y in 2013. The mine broke the world record for long-wall production earlier this year (Leonida, 2014). Finally, the design of mines can impact the energy profile of the mine and need to be a consideration in the procurement of design services for new mines. Consultation note... Experience from the manufacturing sector suggests that the waste or sub-optimal use of energy, often the second largest input after raw materials in that sector, is frequently overlooked in lean problem solving as it is deemed too complex from a technical or organisational perspective (Hammer, Rutten, & Somers, 2014). McKinsey & Company and the Institute for Machine Tools and Industrial Management of the Technical University of Munich have, however, found that analysing the production steps for possible energy wastage and then developing an optimised production process typically results in sustainable energy cost reductions of up to 10–15%, with payback time below three years (LEP, 2014). Although miners are adopting lean principles in their operations as discussed above, information is not readily available on the extent to which energy is a key consideration in the adoption of new operating models based on principles of lean manufacturing.

4.4.2.

Beyond the mine site

System optimisation extends beyond the ROM and across mines to include: 

Open platform development: Anglo American has worked with over 30 other companies on a new in-situ method for mining narrow-vein deposits (Leonida, 2014)



Exploitation of regional proximities to form joint ventures to develop and operate shared infrastructure, thus improving profit margins of existing operations, utilisation of assets and, in turn, return on capital. An Australian example includes the potential Hunter Valley collaboration between Glencore and RioTinto (PwC, 2014b)



Smarter exploration to detect even deeper mineral deposits and modelling deposits with regards to their potential economic assets and challenges right from the earliest stages of exploration. This could have a material impact on the cost:value equation in the industry from exploration through to production.

35



4.5.

Strategy area 3: Business model transformation

With new CEOs at the helm of nearly half the Top 40 mining companies over the last two years (PwC, 2014b), coupled with prevailing industry conditions, it is not surprising that the industry expects new business models to become a key driver of performance. A 2013 survey of 60 mining executives from 25 companies representing $452 billion in 2012-revenue suggested that business model transformation will play a more important role in innovation in the future than at present.22 This is illustrated in Figure 15, reproduced from the 2013 Mining Innovation State of Play survey by Virtual Consulting International (VCI, 2013a, 2013b). Figure 15: Where in the value chain will innovation create the greatest value over the next 10 to 20 years?

New business models adopted by the majors, such as remotely operated and autonomous mining and truckless mines, continue to evolve, whilst real-time information on mobile devices is finding application across the sector. Much of the change is linked to miners adopting ‘big data’ management as a core strategy. We will discuss a number of the emerging themes: 

Autonomous mining supported by on-mine or remote operating centres



Truckless mines enabled by in-pit crushing conveyers



Real-time ‘big data’ transformation

4.5.1.

Autonomous mining

In recent years, a focus in mining innovation has been the introduction of remotely operated and autonomous mining equipment and systems. These technologies represent a class of innovations that involve a step change in the research and development (R&D) effort and are likely to profoundly change how minerals are mined and processed in the future. Automated equipment can be better 22

Mining and mining service company respondents based in Australian based included representatives from: BHPBIlliton, Fortescue Metals Group, Mount Gibson Iron, Gold Fields, Realm Coal, MMG Ltd, Leighton, Ngarda Civil and Mining and the CSIRO. Many other mining companies active in Australia participated from their Head Office locations, including RioTinto, Newmont, AngloGold Ashanti and Anglo American.

36



utilised, operates in a more controlled and precise manner and has a longer useful life, resulting in significant efficiency improvements. In many instances, efficiency improvements translate into reduced requirements for energy and consumables, as well as less waste (Fisher & Schnittger, 2012). Furthermore, it eliminates the need to fly operators to remote mining sites. Consequently, these innovations may initially be driven by factors other than energy efficiency, as their adoption dramatically alters the traditional relationship between capital, labour and energy as a key production input, and can lead to improved energy productivity. Existing innovations range from specific pieces of equipment such as remote-controlled or autonomous vehicles and drilling equipment to entire mines that have been designed and built around automated systems. For example, autonomous haulers are already used by or are planned for RioTinto, BHPBilliton and Fortescue. Autonomous load haul dump (LHD) and truck haulage systems have on-board intelligence and perception technologies, as well as GPS to reduce fuel consumption, extend tyre life, as well as optimise fleet utilisation (Smith, 2014b). Apart from the on-site energy savings, remotely managed sites also reduce the transport cost of ‘fly-in-fly-out’ mine operations that has become prevalent across much of Australia. Rio Tinto’s Mine of the Future™ program aims to automate and remotely control almost all aspects of the company’s Pilbara operations from Perth (See the shaded box showcasing this Rio Tinto initiative in Section 3.1.). The Brisbane Processing Excellence Centre is the latest development in this program; it enables a line of sight to processing data from seven operations around the world (Edwards, 2014). Furthermore, when converting its Argyle diamond mine in Australia from an open cut to an underground mine, Rio Tinto also invested in one of the world's largest automated systems (RioTinto, 2012). A prototype cave tracking system has been installed at Argyle that enables real-time ore flow monitoring for block caves23 (CRCMining, 2014a). Automated underground mining systems typically allow for greater accuracy of cutting sequences in continuous long wall mining and haulage operations, reducing shift changes and operator fatigue. Significant efficiency, productivity and safety improvements in underground mining can also be achieved by investing in automated electric powered underground drilling, scooping and materials movement machines. This kind of equipment can now replace diesel powered underground mining machines, thereby eliminating diesel fumes, reducing the amount of ventilation required and cutting energy demand by up to 90% (Chew, Adkins, & MacGinley, 2013; Mineweb, 2013 & Vella, 2013, cited in Smith, 2014b)

4.5.2.

Truckless mines

In a 2012 statement, BHPBilliton executive Marcus Randolph (Ker, 2012, cited in Smith, 2014a), indicated that the company deems mobile IPCC systems to be transformative in that they will enable virtually ‘truckless’ mine operations: When you run a truck, it takes 10 to 11 employees for every truck. It takes 4½ to five to run it, all the crews that do the maintenance on it, all the camp people that do the camp cleaning and cooking and everything else. If you go truckless (and use input crushers and conveyors) you do not need any of these staff ... at a time when you see increasing diesel prices ... getting rid of trucks or using fewer trucks is desirable Marcus Randolph, BHPBilliton

23

block caving increasingly becoming the method of choice for economically mining a range of massive low-grade deposits, predicting and monitoring caving behaviour is critical to safe and efficient mine operation

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Australian quarry operator Boral (see shaded box below) has been adopting the in-pit crushing conveyers system, as has Brazilian miner, Vale, which is reported to be replacing trucks at some of its Brazilian iron ore mines with IPCCs. Replacing haul trucks with in-pit crushing conveyers has the potential to reduce energy costs by up to 70%, but also yields significant labour productivity and maintenance gains. In-pit crushing conveyers replace the need for many haul trucks, which also reduces water consumption as less water is needed for dust suppression in open-cut mining (Smith, 2014a).

Box 13: Anatomy of a truckless system

Reproduced from Australian Bulk Handling Review, 2013 Boral’s strategy is to optimise its quarrying process by moving away from the traditional load and haul methodology. By adopting in-pit crushing conveyer systems, it has been able to reduce the number of trucks and people moving between the blast site and the fixed crushing plant. In a conventional crushing plant, a drill and blast team blast the shot and develop a muck pile. A front-end loader at the muck pile loads haul trucks, which transport the rock to a fixed primary crusher. With the in-put crushing solution at Peppertree, an excavator located on the muck pile loads material directly into the Lokotrack’s hopper. The rock moves along a grizzly feeder that passes undersized rock directly onto the machine’s outbound conveyor. Only the large rock that needs to be crushed passes through the jaw crusher. In this way, energy isn’t wasted on passing small material through the crusher.

Metso’s Lokotrack LT160 in-pit crusher for Boral’s Peppertree quarry Crushed rock is then transported to the fixed, in-pit belt conveyor via two mobile conveyors. The fixed conveyor carries crushed rock from the in-pit crusher to the fixed plant for further processing. After the blast, a wheel loader cleans the quarry floor and the Lokotrack moves to the new muck pile. The in-pit crusher can be relocated in minutes by an operator via a remote console worn around the operator’s waist. (Australian Bulk Handling Review, 2013).

4.5.3.

Real-time ‘big data’ transformation

Transforming ‘big data’, including information on ore grade, fleet, production, financials, safety, equipment temperature and fuel consumption, into real-time information to support operational decision-making will become a key differentiator for high-performing mines. Real-time information to support effective decision-making on site has already brought about a stepchange in Fortescue Metals Group’s Cloudbreak iron ore mine. Supervisors have intuitive visual 38



dashboards at their fingertips, so that issues can be rectified mid-shift (e.g. moving trucks from different pits to optimise the fleet and maximise productivity). IT News reports that Fortescue’s fleet of RH340 diggers each produced over 5500 tonnes per hour over the first three months of 2014, up 11%, while its trucks are hauling over 70 more tonne-kilometres per truck every week. Fortescue expects to realise $30 million in annual cost savings from the real-time reporting of productivity data to the mobile devices of its field operations team (Winterford, 2014). Consultation note... Do we understand the full benefit case for ‘big data’? Evidence of the ‘energy specific’ application of ‘big data’ on mines is not readily available. Industry views and contributions to enhance the evidence base will be sought during the 2xEP consultation process.

4.6.

Strategy area 4: Preserve/increased output and quality

Quality in this context relates to both the product, as well as the real and perceived impact of the output on the quality of the environment or society in general. Most of the systems optimisation and transformative business models will, as discussed, have as their explicit intent, increased throughput. Some of the improvements and emerging models also have an impact on the ‘quality’ of output from a societal perspective, for example: 

Anglo American’s Mogalakwena platinum mine, i.e. reduced waste, as discussed earlier



Improving the efficiency of crushing and grinding ores by pre-concentration improves throughput, but also reduces water requirements and, therefore, pumping requirements (Smith, 2014a)

Emerging markets, such China and India, are key customers of Australian coal and iron ore exports. Changing environmental standards in these export markets suggest that value-adding activities such as washing coal to reduce sulphur content or grinding out impurities before shipping iron ore will become important in preserving market share. As reported by PwC in Mine 2014, northern Chinese steel mills that typically use low quality iron ore are struggling to limit carbon emissions from blast furnaces. This is resulting in a push for so-called ‘green iron ore’ to address pollution concerns in major Chinese cities. Suppliers of iron ore are being encouraged to deliver a blend of ore that will reduce emissions (PwC, 2014b). Responding to this key customer’s demands will be particularly important for Australian miners in the current supply environment.

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Consultation note... This section presented a range of opportunities, but we recognise that the type of mine, size and technological sophistication vary significantly. The pathways to energy productivity improvement are, therefore, likely to be different. So, where is the common ground? Is there scope to continuously improve the sector’s productivity if the industry combines resources (i.e. time, knowledge and investment) in: 

signing up to specific standards (e.g. data communication)?



promoting best practices and establishing performance benchmarks?



progressing specific emerging technologies?



other?

Ultimately, is there sufficient commonality to develop a series of pathways targeting energy productivity opportunities and barriers for industry or ‘groups’ of miners?

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5.

Barriers to energy productivity Please note...

This section is intended to provide a starting point for engagement with mining sector stakeholders in considering what action the industry could take to address barriers and where action or support may be required from government to remove or reduce such barriers.

Australia’s METS sector is a world leader in energy-efficient equipment, technology, services and knowledge. Investment in innovations has led to world-class solutions for improved efficiency in mining. However, take-up rates of these energy-efficient technologies in Australia are low and, according to CEEC, in some cases these technologies have been more widely adopted in other countries. It is imperative that barriers to the adoption of new technologies and improved energy productivity are overcome to improve returns on research investment and maintain the competitiveness of the Australian mining sector. The primary reasons for a lack of focus on energy productivity in the Australian mining sector to date are: 

Energy cost is not a ‘big enough’ issue; a small share of operating cost



Short payback thresholds for investments for ‘non-core’ assets



Management practices and cultural barriers (i.e. the way things are, or have always been, done in the company or industry)



Split incentives for energy efficient site development and operations



Information, knowledge and expertise.

Each of the above barriers will be briefly discussed below.

5.1.

Energy is not a ‘big enough’ issue

Rapid change in the mining sector over the last 10 to 15 years has masked significant changes that have also occurred in the energy sector over this period, reflected in the three distinct stages below: 

Era 1 – energy is cheap and therefore viewed as a small fixed overhead to production



Era 2 – energy cost started to increase, but with healthy margins during the peak of the commodities boom (or super cycle) from 2005 to 2013, mine managers’ focus remained steadfast on growing output whilst operating costs were a lower order consideration



Era 3 (starting 2013) – commodity prices ‘normalise’, whilst the focus remained on volume throughput to maintain revenues. With declining margins, miners recognised the need to reduce operating costs/tonne in order to remain profitable.

Although energy cost may still be as low as 5–10% of total operating costs (see Figure 5) falling commodity prices and declining margins, mean that the management of energy cost is now a significant issue, especially for marginal mines (see Figure 6).

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5.2.

Short payback threshold for investments

Quarterly performance expectations place pressure on short ROI cycles. This results in short-term decision making while energy productivity strategies often require longer ROI periods. Furthermore, with the deterioration in mine profitability in FY 2013 (Figure 6) and the reported drop in return on capital employed (ROCE) by the Top 40 miners to 5% as at December 2013,24 investor sentiment has shifted and shareholders are now placing pressure on mines to improve returns in the short term (KordaMentha, 2013; PwC, 2014b). Although the typical mine life and planning horizon is very long, reporting cycles are shorter and this is clearly a time when the focus of miners will shift towards: 

Reduction in operating expenditure, beyond ‘quick fix’ headcount reductions



Added scrutiny of capital investment and deferment as management is more likely to continuing running operations with old and possibly inefficient equipment as persistently low commodity prices may shorten the productive life of a mine site.

However, the unrealistically short payback periods (as short as one to two years) often demanded in Australia hinder investment in sustainable energy productivity gains. This is partly an internal company issue, but it is exacerbated by the terms available from commercial lenders. Mainstream financiers typically do not recognise cash-flow benefits associated with energy projects, whilst the loan duration of three to five years is often significantly shorter than the useful life of the equipment.

5.3.

Management practices and cultural barriers

One hundred per cent of participants in the 2013 Mining Innovation State of Play Survey recognised that innovation is key to meeting corporate objectives. However, 73% indicated that management focus is on ‘incremental innovation’ and 69% focus on innovation efforts over a zero to three-year period. The headline findings from this survey are reproduced from the Virtual Consulting International report as Figure 16 below (VCI, 2013b). Figure 16: Headline results from the 2013 Mining Innovation State of Play survey

24

Compared to 10% in 2009 during the global financial crisis.

42



Miners’ perceptions of the historical success of innovation at their operations (i.e. only 25% are deemed successful) may contribute to greater risk aversion, possibly explaining in part why many of the opportunities discussed in the previous section have not been adopted broadly by miners. This trend may be partly explained by the prolonged ‘mining boom’, impacting the way mining businesses operate, as reflected in a quote from Ernst & Young in their Business risks facing mining and metals 2014–15: The super cycle lasted for so long it had the impact of altering the DNA of mining companies to adapt the processes, performance measures and culture solely toward growth. The size and scale of the problem is too large for conventional single point solutions to work. To attain the improvements needed for sustainable productivity gains at profitable growth levels requires broad business transformation (Ernst & Young, 2014)

The above quote amplified CEEC’s finding during their 2012 roadmap development process. They found a focus on maximising throughput at almost any cost. Consequently, current organisational practices do not encourage maximising efficiency. Many mining companies also suffer from ‘silo structures’, with weak accountability for energy efficiency across these silos. With obvious exceptions, CEEC’s finding confirmed the generally conservative, risk-averse nature of the industry, which contributed to a reluctance to adopt new technologies or support alternative strategies. Finally, a lack of systems knowledge in the face of increasing systems complexity provides little incentive to be an early adopter, with the gap between project owners and engineers on one side and technology developers on the other hindering innovative technology transfer (Tim Napier-Munn, 2014). These issues identified by CEEC are in sharp contrast to the list of attributes of ‘successful companies in addressing the productivity challenge’ as listed in the recent Ernst & Young report, some of which are listed below: 

Bold, not incremental



Take an end-to-end view



Eliminate silos



Learn from history, but be open to innovation (Ernst & Young, 2014)

5.4.

Split incentives for energy efficient site development and operations

Unless energy is a key consideration in contracts with mine designers, developers and operators, the long-term energy profile of mines can be adversely impacted and energy cost becomes a driver of operating expenses. A soon to be published guide produced by the Department of Industry illustrates this point by means of an example in which a mine owns and operates the mills, but contracts out the extraction and transport of ore bodies from mine-to-mill on a $/tonne basis. This KPI in itself does not consider the energy cost associated with crushing and grinding rocks into smaller particle sizes. Spending more on smart blasting to break up ore bodies into smaller particle sizes could save much more energy (and cost) in the crushing and grinding phase of mineral processing (Smith & Stasinopoulos, 2014).

5.5.

Information, knowledge and expertise

There is no doubt that the mining industry employs some of the smartest, most talented and sophisticated managers and professionals. However, there is a perception that the industry has 43



‘decimated’ its comminution knowledge base in recent years (Tim Napier-Munn, 2014). Furthermore, ‘silo’ structures, as discussed above, limit the cross pollination of ideas, shared insights and understanding of ‘the whole picture’. Lack of site-level awareness of the structure of energy contracts and the impact of peak demand charges on the total cost of electricity, in particular, can undermine energy productivity programs (e.g. energy savings do not translate into financial savings if consumption constitutes less than 50% of total electricity charges.) Furthermore, unless companies use comprehensive energy-auditing systems on an enterprise-wide basis, the true energy cost of operations will be difficult to determine. This is not a common practice. Therefore building a business case to justify investment in more energy productive systems is challenging.

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6.

Overcoming the barriers Please note...

This section is intended to provide some ideas for discussion with mining stakeholders in the course of developing the 2xEP roadmap over the next six months. This section is not intended to prescribe solutions. It provides an initial ‘list’ of potential concepts for a co-ordinated sector-wide program.

Barriers typically cannot be addressed independently of each other. Unless business is confident about its future, it will not invest; if staff on sites do not have suitable data, they will not be able to make business cases confidently; without the skills and training to use information, they will not be able to design effective solutions; and without good quality business cases, finance will not flow to fund capital projects. Multiple barriers need to be addressed simultaneously. The areas for consideration are discussed under the following headings: 

Collaborative innovation



People and organisational capabilities



Investment on energy programs



Incentives



Regulation and standards



Other considerations.

6.1.

Collaborative innovation

The A2SE 2xEP Roadmap considers innovation in its broadest context, including technological, process and business model innovation. It is therefore central to all four strategic areas of focus for improving energy productivity. The NSW Government’s support for industry-led Innovation Hubs is well-timed to exploit the significant opportunities to increase the value-add of products and services delivered by the Australian economy through enhanced partnerships. The first of these hubs, the NSW Energy Innovation Knowledge Hub, based at Newcastle Institute for Energy and Resources (NIER), was launched in September 2014. CSIRO Mining also carries out strategic research into technologies that maximise the long term value of resources. A recent report on Industry Research Collaboration highlights that 80% of Australian business leaders believe that innovation is the main driver of a competitive economy and that businesses engaging in collaborative innovation with research organisations are more likely to report increases in productivity (NSW Business Chamber, 2014). This is particularly relevant to the mining sector in light of the 2013 Mining Innovation State of Play Survey results discussed earlier, and the R&D spend by the mining industry:

45



Mining is significantly lagging behind other industries when it comes to innovation. For example, our total R&D spend is probably 10% of what the global petroleum sector is spending this year. If we don’t make step changes in technology, leadership practices and production, someone else will. The organisation is the starting point for change...This sort of change (open platform collaboration) is imperative to the future of the mining industry … working to achieve a common goal and no one will get to keep the intellectual property. Initially, it was a painful process to establish this, but it has yielded huge gains and going forward, this type of approach will be key. Mark Cutifani, CEO Anglo American, cited in Leonida, 2014

Many industry players already recognise this and are not only investing in research, but have been implementing cutting-edge solutions from such collaborations. For example, RioTinto embraced this philosophy back in 2007 when it established the Rio Tinto Centre for Mine Automation (RTCMA) at the University of Sydney, funded by Rio Tinto with $21 million for an initial period of five years. It focuses on robotics, sensing technologies, data fusion and systems engineering. RTCMA is one of a number of research centres with links to universities funded by Rio Tinto (Fisher & Schnittger, 2012). Mechanisms through which business, industry and research institutions can collaborate on innovative solutions can also provide a platform for information sharing and capacity building. However, this will require investment in knowledge aggregation and distribution systems built around communities of interest, bringing together the many great initiatives already underway, such as CEEC International Ltd. Please consider... Innovation and knowledge hubs exist around the country and the globe. What needs to be done to ensure knowledge is shared and linked, and funding does not duplicate existing programs?

6.2.

People and organisational capabilities

Energy productivity first and foremost must come from corporate and mine-site leadership, reinforced by organisational performance-management practices. Energy productivity needs to be considered as a cross-functional metric and accountabilities assigned accordingly. CEEC International has already done extensive work in this regard focussed on comminution (see shaded box below)

Box 14: Existing CEEC Roadmap

The CEEC industry roadmap, developed in 2012, proposed four steps: 

Measure performance



Adopt best-practice technology



Implement appropriate business drivers and KPIs



Communicate the benefits, motivate, engage and train

46



Recruitment practices are an important determinant of on-the-job productivity. Individual differences between operators, identifiable during the selection and recruitment process, can account for roughly 14% of output produced by mining equipment (PwC, 2014b). Furthermore, the role of formal and onthe-job training programs to support an energy productivity agenda will also be important. Good examples of programs already available include: 

JKTech, the technology transfer company for the Sustainable Minerals Institute (SMI) at the University of Queensland, offers a range of courses and training on plant optimisation and sustainable productivity.25



Sustainable Minerals Institute – Centre for Social Responsibility in Mining (CSRM) provides tailored training on social aspects and impacts of extractives and energy projects. The training is designed to suit a range of groups, from frontline community relations practitioners to community representatives, government officials and regulators, journalists as well as industry executives. Short courses and master classes are designed to build capacity across the industry and up-skill external stakeholders to engage with industry in a productive way.



Australian TAFE Certificate IV qualification Automation Technician, developed in response to the rapid adoption of automated mining practices. This course targets electrical workers wishing to up-skill in instrumentation, digital technology, process control, SCADA and human machine interface (HMI) in automated industrial applications (CRCMining, 2014)

6.3.

Investment in energy programs

Until the last 12 months, external debt finance was not readily available for energy projects. The Big 4 banks are gradually coming to grips with some energy asset classes, often with the support of the CEFC. Some financial institutions are now offering attractive debt financing (particularly to their existing customers) with terms of up to seven years. Off-balance-sheet options are also becoming more common e.g. third-party build/own/operate models where clients enter into power purchase agreements. Nonetheless, there are still some major obstacles in this area. Key among them are: 

Understanding of energy use in key processes at a mine site



Reducing the perceived risk of energy projects



Overcoming the relatively small scale of many energy projects, which makes them unattractive to financiers and not ‘deserving’ of management attention given the perceived ‘bigger’ opportunities in other parts of the operation



Turning energy-saving ideas into compelling business cases for financing, internally and externally.

Where novel approaches are being developed to close the financing gap, it is critical that the approaches and lessons be widely communicated through case studies.

6.4.

Incentives

There is reliable evidence that incentive programs motivate companies to invest in improved energy productivity. These can be in the form of grants, tax incentives, white certificate programs and other 25

http://www.minemanagers.com.au/sb_cache/associationnews/id/17/f/mirm

47



external funding. But these programs are expensive and need to be funded. Generally, this funding comes either from government-consolidated revenue (taxpayers) or from energy users (through small environmental charges in retail tariffs or wholesale energy prices). The past two years have seen the conclusion of most Commonwealth Government programs and it is not expected that the current government will introduce significant new programs (Department of Industry, 2014a). The exception is the Commonwealth’s Emissions Reduction Fund (ERF), which offers financial incentives in the form of payments per tonne of carbon abated. The first auction awarded contracts at an average price of $13.95 per tonne of abatement (Department of the Environment, 2015). Thus, the ERF could provide competitive incentive payments for energy productivity improvements, but it is unlikely to have an impact on energy project viability. The ERF legislation could eventually require carbon-intensive companies to cap their emissions. The rules for the operation of the safeguard mechanism should be released in October 2015, however it will not commence until 1 July 2016 (Innes, 2014). Please consider... Application for approval of a methodology is costly and in most cases will not justify the investment for a single company. Is there scope and interest for industry-wide approved methodologies under the ERF?

Given the uncertainty in revenue due to commodity price volatility and the associated impact on mine life, miners are typically risk averse when it comes to capital intensive projects. In spite of the long term benefit of reduced operating cost major capital projects, such as electrification of mine operations (e.g. moving from trucks to conveyers powered by hybrid diesel-renewable system) are unlikely to be implemented in the prevailing market conditions without some form of incentive (e.g. accelerated depreciation).

6.5.

Regulation and standards

In the current political environment, regulation is not generally accepted as a policy to achieve change in markets (Department of Industry, 2014a). While the 2xEP program will prioritise other mechanisms to drive change, well-targeted and designed regulation should be considered, as it can be costeffective in accelerating market transformation e.g. use of minimum performance standards for equipment (see shaded box). Furthermore, policy certainty on matters such as the diesel rebate is required.

Box 15: Performance standards for industrial equipment... The Equipment Energy Efficiency (E3) program has been predominantly focused on domestic appliances. It was estimated in 2010 that minimum energy efficiency performance standards (MEPS) applied to industrial and manufacturing equipment could save at least $1.5 billion per annum in industry energy costs and provide annual greenhouse abatement of up to 2.8 Mt CO2e (COAG, 2010, cited in Smith, 2013). Increasing coverage of industrial products beyond certain classes of motors and drives is planned. Electric and gas process and industrial equipment standards are now projected to account for 33% of the estimated 101.9 PJ energy savings attributed to the E3 program between 2014 and 2030 (Department of Industry, 2014b).

Suppliers also play a key role, as illustrated by Caterpillar and Komatsu in the advent of autonomous trucks. Optimising data flow across the diverse set of operational technologies and asset classes is 48



essential for real-time decision making, but the associated technology investments to ensure compatibility can be a huge cost driver. Industry and government support for initiatives to drive common communications and data exchange protocols and standards will become increasingly important to ensure that the benefits of ‘big data’ are available to miners of all sizes in the years to come. There are many other examples of regulation used internationally to drive energy efficiency. For example, in the UK and Germany there is a requirement for companies to voluntarily enact measures to improve energy efficiency (and in Germany to implement energy management standards) to avoid paying a significant tax. In Canada, utility companies partner with mining companies to support energy audits and improvements programs.

6.6.

Other considerations

6.6.1.

Address energy competitiveness issues arising from escalating energy prices

While not included in the formal scope of work for the 2xEP program, industry has expressed concern that this program also recognise and communicate other element of the energy competitiveness issue i.e. how governments should respond to increasing energy prices, as efforts to reduce energy prices in the medium term would greatly assist efforts to improve energy competitiveness in parallel with measures to improve energy productivity. It is proposed that 2xEP communicate the need for action to minimise energy prices in order to improve competitiveness, alongside our main message of doubling energy productivity.

6.6.2.

Role of co-generation and renewable energy

Defining the role of on-site renewables (wind, solar PV and solar thermal) in improving energy productivity in the mining sector needs further consideration. With regard to the secondary energy productivity metric, this could include consideration of renewable energy as a hedge against future energy cost rises.

49



7.

Next steps

This report establishes a starting point for discussion with (and amongst) mining sector stakeholders to address the opportunities, barriers, policy recommendations and a potential 2xEP implementation plan for the mining sector. Key issues for consultation include: 

Agreeing the metrics for measuring energy productivity improvement in the sector (and determining whether different metrics are needed for sub-sectors), and cascading metrics down to plant level.



There is sufficient evidence that a step change in energy productivity, relative to current trends, is achievable. This provides a starting point for discussion. More detailed analysis of opportunities in mining sub-sectors, with due consideration for the likely return on investment from these opportunities could assist in providing a firmer estimate of the likely scale of commercially attractive opportunities.



Agreeing an energy productivity improvement target for 2030 for the sector. Whichever target is set, it will also be important to set milestones for achievement year by year and a process for tracking progress.



Defining the barriers (and they may between sub-sectors) and developing a detailed and integrated industry-led program to overcome these barriers and support businesses to make substantial energy productivity savings.



Implementing initial programs during the 2xEP Roadmap development activity if possible. Particular consideration could be given to designing and launching a voluntary leadership and recognition program (‘2xEP Challenge’) in parallel with implementing the energy productivity pathways.



Developing recommendations for government policy measures to facilitate 2xEP achievement by business.



Modelling the costs and benefits of recommended measures.



Modelling the total benefits of the suite of measures for the mining sector.



Communicating the outcomes of the industry roadmap and marketing the benefits of implementing the program.



Delivering and measuring the outcomes.

A2SE is looking forward to working with mining sector stakeholders to scope opportunities, consider options and drive improvement in energy productivity.

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Appendix A.

Abbreviations and acronyms

ABS

Australian Bureau of Statistics

AEMO

Australian Energy Market Operator

AIP

Australian Institute of Petroleum

ANZSIC

Australian and New Zealand Standard Industrial Classification

boe

barrel of oil equivalent

BREE

Bureau of Resources and Energy Economics

CEEC

Coalition of Eco-efficient Comminution

CRC ORE

Co-operative Research Centre for Optimising Resource Extraction

DSR

Demand Side Response

EEO

Energy Efficiency Opportunity (Program)

EIA

(US) Energy Information Administration

GDP

Gross Domestic Product

GVA

Gross Value Added

IPCC

in-pit crushing conveyers

MCA

Minerals Council of Australia

NRCAN

National Resources Canada

OS

overburden slushers

NRMA

National Roads & Motorists' Association

RBA

Reserve Bank of Australia

R&D

research and development

ROM

run of mine

ROCE

return on capital employed

SAG

Semi-Autogenous Grinding

SMI JKMRC

Sustainable Metals Institute Julius Kruttschnitt Mineral Research Centre

TGP

Terminal gate prices

TMM

Tonnes material mined

USA

United States of America

59



Appendix B.

Conversions

Reproduced from BREE (2014a) UNITS Metric units

Standard metric prefixes

J

joule

k

kilo

103 (thousand)

L

litre

M

mega

106 (million)

t

tonne

G

giga

109 (billion)

g

gram

T

tera

1012

Wh

watt-hours

P

peta

1015

b

billion (1000 million)

E

exa

1018

STANDARD CONVERSIONS 1 barrel = 158.987 L 1 mtoe (million tonnes of oil equivalent) = 41.868 PJ 1 kWh = 3600 kJ 1 MBTU (million British thermal units) = 1055 MJ 1 m3 (cubic metre) = 35.515 f3 (cubic feet) 1 L LPG (liquefied petroleum gas) = 0.254 m3 natural gas Conversion factors are at a temperature of 15°C and pressure of 1 atmosphere. INDICATIVE ENERGY CONTENT CONVERSION FACTORS Black coal production

30 GJ/t

Brown coal

10.3 GJ/t

Crude oil production

37 MJ/L

Naturally occurring LPG

26.5 MJ/L

LNG exports

54.4 GJ/t

Natural gas (gaseous production equivalent)

40 MJ/m

Biomass

11.9 GJ/t

Hydroelectricity, wind and solar energy

3.6 TJ/GWh

3

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Appendix C.

Key end-use energy applications on mine sites

The table below provides a brief summary of energy end-use applications on mine sites, with reference to other studies. However, it should be kept in mind that end uses vary across mine types. Comminution (crushing and grinding)

Comminution of gold and copper ores is estimated to represent 1.3% of Australia’s electricity consumption and up to 52% of mine site electrical power, or 36% of total mine site energy (Ballantyne & Powell, 2014b; Curry, Ismay, & Jameson, 2014; NapierMunn, in press). Similar estimates are provided by Natural Resources Canada, namely 45% of the energy used in a typical open-pit mine operation is spent in rock size reduction. The distribution of energy within this process shows that blasting accounts for 3–5%, crushing for 5–7%, and grinding for 90% of the total energy used (Natural Resources Canada, 2013). Grinding mills are driven by diesel off-grid. Much of Australia’s off-grid diesel consumption is related to running the grinding mills.

Materials handling (diesel)

Electricity used in conveyors and underground haulage systems is the biggest energy cost for materials handling for underground mines, whereas much of the equipment used in the transfer or haulage of materials in open-pit mining is powered by diesel engines. Equipment includes service trucks, front-end loaders, bulldozers, bulk trucks, rear-dump trucks and ancillary equipment such as pick-up trucks and mobile maintenance equipment. Diesel technologies are highly energy intensive, accounting for more than 80% of the total energy consumed in materials handling (see Figure 13). In Australia, as of 2008–09, 40 reporting Energy Efficiency Opportunity (EEO) Program companies in the mining sector consumed 308 PJ of energy, of which 52.5 PJ was diesel (17%) for haulage and electricity generation (Department of Energy, Resources and Tourism, 2010a).

Ventilation

This area applies only to underground mines, resulting in the understatement in Figure 13 of its importance. In underground mining, ventilation can account for between 25– 50% of a mine’s energy consumption (Shonin and Pronko, 2013).

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Box 16: Useful resource highlighting energy use improvement opportunities across the above areas The EEO Significant Opportunities Register – Mining provides a listing of some of the significant opportunities identified by mines as part of the EEO process. The table can be filtered to find specific types of opportunities and is available at http://energyefficiencyopportunities.gov.au/files/2013/01/MiningSignificant-Opportunities.xls A report commissioned by the Australian Government, Department of the Environment and Water Resources, entitled Energy Efficiency and Greenhouse Gas Reduction contains a good description of many common energy-efficiency opportunities and good energy-management practice. This report is available at http://www.commdev.org/energy-efficiency-and-greenhouse-gas-reduction The National Resources Canada’s Green Mining Initiative is also a good resource for best practices from global industry. A high level overview of this initiative is available at http://ec.europa.eu/DocsRoom/ documents/6449/attachments/1/translations/en/renditions/native%20

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Appendix D.

Supplementary material on the productivity of the mining sector

Mining is characterised by high labour productivity relative to other sectors in Australia, in absolute terms (i.e. $-value of output relative to labour cost). This is not unusual given the capital intensity of the sector and is largely reflective of the characteristics of the sector. However, the trend in the historical multifactor productivity (MFP) index of the resources industry has been downward, as is illustrated in Figure 17, which draws a comparison between the resources sector and the Australian market sector for the last 18-years (ABS, 2013c). Figure 17: Decline in the mining sector MFP

200

MFP h ours worked basis (Index 2011-12 = 100)

180 160 140 120 100 80 60 40

B Mining

Market Sector industries (Divisions A to N, R and S)

This general trend is not unique to Australia, with similar declines recorded in the USA and Canada (Grafton, 2013). Two recent PwC studies attribute poor productivity performance in the mining industry to its inability to execute strategy, align capital and resource allocations, poor decision making and underutilisation of equipment (PwC, 2014a, 2014b). However, results from BREE decomposition analysis indicates that mining MFP grew by 2.5% per annum between 1985–86 and 2009–10 if the effect of output quality depletion and production lags are taken into account (BREE, 2013). The following section provides additional information on factors that impact the development of an energy productivity roadmap in the Australian mining sector now that the commodity cycle is turning from investment to production. These factors are: 

Declining ore grade (metal per tonne of ore)



Decline in major new discoveries



Increased investment, and whilst commodity prices are falling.

63



Declining ore grade Whilst the life of known reserves may extend over many years, remaining deposits are typically of a lower grade (Productivity Commission, 2013), as illustrated in the shaded box below.

Box 17: Declining ore grade for base and precious metals in Australia The declining ore grade for Australian base and precious metals is evident from the figure below, derived from a detailed analysis of minerals production in Australia since the 1840s. The long-term trend in average ore grades has been down for copper, gold, lead, zinc, uranium, nickel and silver. In addition, there has been a dramatic increase in the extent of overburden removal required for coal, copper, gold and uranium since the mid-20th century and especially since the 1980s (Mudd, 2009, as cited in Fisher & Schnittger, 2012).

Reproduced from Fisher & Schnittger, 2012

Decline in major new discoveries Some experts estimate that half of Australia’s existing mines could close in the next seven to 18 years (Schodde, 2012), whilst it can take up to 20 years to convert a discovery into a mine. The last decade was characterised as a period of increased exploration efforts as illustrated in Figure 3 with reference to both ‘brown field’ (existing deposits) and ‘greenfield’ (new deposits) (ABS, 2014d). Coal and iron ore’s share of exploration by minerals sought increased notably over this period, with a significant decline in gold and other base metal exploration expenditure (Minerals Council of Australia, 2014b). There has been a sharp drop in activity since 2012, with a further 10% drop in exploration capital expenditure predicted for the 2014 financial year (PwC, 2014b). Since the mid-1990s, the real cost per exploration metre drilled increased substantially, as illustrated in Figure 18 below (ABS, 2014e, 2014f), whilst major new discoveries are declining (see shaded box below).

64



400 350 300 250 200 150 100 50 Sep-1988 Jul-1989 May-1990 Mar-1991 Jan-1992 Nov-1992 Sep-1993 Jul-1994 May-1995 Mar-1996 Jan-1997 Nov-1997 Sep-1998 Jul-1999 May-2000 Mar-2001 Jan-2002 Nov-2002 Sep-2003 Jul-2004 May-2005 Mar-2006 Jan-2007 Nov-2007 Sep-2008 Jul-2009 May-2010 Mar-2011 Jan-2012 Nov-2012 Sep-2013

Real cost per metre drilled (2012 prices)

Figure 18: Increase in real cost per metre drilled

Box 18: Major new discoveries in Australia are falling The number of ‘giant’ and ‘major’ discoveries in Australia is falling, as exploration expenditure rises (see figure below for mineral discoveries, excluding iron ore, coal and petroleum). Australia’s share of the western world’s giant discoveries has fallen from around 17% in the 1980s to around 6% in the 1990s. It is estimated that as much as half the exploration spend by Australian miners is made outside the country. In dollar terms, Australia’s share of global non-bulk mineral exploration, which excludes iron ore and uranium, also dropped from around 19% in the early 1990s to the current level of around 9% (Productivity Commission, 2013).

Reproduced from Productivity Commission, 2013

In the Australian mining industry, there are fewer new resources coming online to displace the old ones, which are, on aggregate, reporting declining ore grades, as discussed on page 64. Given the 65



increased energy intensity of mining and processing lower grade ore and the decline in the discovery of new major resources, increased energy intensity of mining production is likely to be a feature of the Australian mining sector in the decades to come unless the industry finds new high quality resources or ways to improve the energy productivity of the industry. When commodity prices were at an historic high, the increased energy intensity of mining production was not a major concern. However, forecast price levels for key commodities are trending down as discussed below, with gold at an all-time low.

Increased investment, and whilst commodity prices are falling Changes in export prices explain approximately three-quarters of the fluctuations in the growth of export values since 1990. Developments in export prices can therefore have a significant impact on export earnings and economic activity in Australia (RBA, 2014a). Commodity export prices can be volatile. The bulk commodity and base metal prices were at long term historical highs between 2006 and 2011, as illustrated in Figure 19 (RBA, 2014). Since then, prices have declined sharply, with gold experiencing a 27% drop, the largest in 30 years (KordaMentha, 2013; PwC, 2014b). Figure 19: RBA weighted commodity price index for base and bulk commodities26

250

Index 2012/13 = 100

200

150

100

50

Base metals prices – A$ Index

Jul‐2012

Oct‐2013

Apr‐2011

Jan‐2010

Oct‐2008

Jul‐2007

Apr‐2006

Jan‐2005

Oct‐2003

Jul‐2002

Jan‐2000

Apr‐2001

Oct‐1998

Jul‐1997

Apr‐1996

Jan‐1995

Oct‐1993

Jul‐1992

Apr‐1991

Jan‐1990

Oct‐1988

Jul‐1987

Apr‐1986

Jan‐1985

Oct‐1983

Jul‐1982

0

Bulk commodities prices – A$ Index

Mineral processing requires large capital equipment investments and mining companies face the challenge of achieving their targeted return on investment for these expenditures regardless of external market pricings. As price takers, periods of high commodity prices made it desirable from the perspective of value of a mining stakeholder to drive increased throughput in spite of the increased cost of mining lower grade ore. During the ‘mining boom’, the sector made significant investments in developing new mines and infrastructure, as well as expanding existing mines. Capital investments of this nature are ‘lumpy’, with a lag between investment and production. In the short term, this lag contributes to the decline in capital productivity of the industry as measured in official Australian productivity statistics (see Figure 17). 26

Base metals: aluminium, lead, copper, zinc and nickel; Bulk commodities: iron ore, metallurgical coal and thermal coal. The above series excludes alumina, gold and copper ore (copper is not included in the data series).

66



As the five-year peak investment phase is drawing to a close, increased output is starting to come online. Nearly half of the over $400 billion of resources, energy and related infrastructure projects undertaken in Australia over the last decade are now operational. Approximately $220 billion27 of projects is still under development (BREE, 2014b). Additional supply from new projects coming online is likely to add to the downward pressure on commodity prices. The September 2014 BREE Quarterly Review reported that project completions in just the past 12 months delivered more than 200 million tonnes of iron ore and 40 million tonnes of coal (BREE, 2014b). However, the increases in iron ore and coal output in particular, as illustrated in Figure 20 ( BREE, 2014b), have been underway for the last decade. Figure 20: Increase in Australian resources and export volumes

Index graph reproduced from BREE, 2014b Commodity

Between 2003/04 and 2008/09

Since 2008/09 to 2013/14

Iron Ore

66%

101%

Thermal coal

28%

43%

27

Note this includes energy (i.e. oil and gas).

67


2xEP Mining Sector - Overview

2xEP Mining Sector - Overview

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