June 2017

Common factors in the implementation of new technology in the mining industry

  • By A T Job FAusIMM(CP) and P R McAree, School of Mechanical and Mining Engineering, The University of Queensland

This is an excerpt from a paper to be presented at Iron Ore 2017, which will be held in Perth from 24-26 July. Visit the Iron Ore 2017 website for more details on the conference program and registration.

There is significant value at stake in the mining industry from the implementation of new technologies that support the enhanced profitability and sustainability of mines. However, in order to realise this value, new technology must be implemented in a way that is both effective and sustainable. The industry has a mixed history for technology implementation that provides fertile ground for understanding what is necessary for innovation to deliver value. At the Iron Ore 2017 conference in Perth, we will present a paper that describes early stage research investigating this why this is so, with the aim of improving how to deliver value. Several case studies will be provided, covering both successful and unsuccessful technology interventions. The paper will identify the common factors that emerge from the case studies, and offer a path forward for further research in this area.


The performance of mining operations globally, in general, have not improved over the last decade. Industry-wide return on capital employed (ROCE) trended down from 20 per cent in 2007 to just four per cent in 2015 (O’Callaghan, Burkitt and McKenna, 2016). Similarly, global mining productivity declined, on average, by 3.5 per cent per annum, from 2004 to 2013 (Lala et al, 2015). This trend is further highlighted by the Australian Bureau of Statistics (ABS) Multi Factor Productivity (MFP) index (Figure 1). The impact on the sustainability of the industry from this poor performance is potentially significant. It is important to consider what actions need to be taken within mining operations in order to counter these trends and deliver enhanced industry value.


A range of metrics can be applied to measure enhanced industry value at mining operations: profit, free cash flow (FCF), capital expenditure (capex), ROCE, and net present value (NPV) among others. The ability to positively influence these metrics is a complex challenge exacerbated by the often inverse relationship between these metrics.

For example, a focus on short-term (within one financial year) FCF may negatively impact on the mines life-of-mine NPV (NPVLOM). This challenge is further complicated by competing business priorities. For example, a mine operator may seek to deliver a sub-optimal profit level, if it means that a safer or lower risk and more sustainable mine can be delivered over the long-term. Equally, a mine operator may take less interest in long-term sustainability if instead short-term cash flow is a critical priority for the mine’s immediate survival.

However, within this complex dynamic, we argue that over the long-run, it is ultimately the maximisation of the NPVLOM that every mine operator should seek to deliver. This focus on an all-encompassing NPVLOM takes into account factors including cost minimisation and recovery maximisation. This approach, at least in theory, results in the highest level of value being achieved (Whittle, 2009).

To maximise NPVLOM there are a broad range of strategies that can applied to a mining operation. These strategies can be complex and multifaceted. However, we argue that any strategy implemented can be categorised into one of four general strategy types (Table 1).

Within these four strategy types, we exclude from our scope any further consideration of enhancing value through economies of scope or through improving the resource quality. These strategies are excluded as a result of the limited ability that a mining operation has to implement these strategies. Limiting ourselves to the strategies that are site controllable leaves two strategy types for further consideration. Either a mining operation can deliver enhanced NPVLOM through realising economies of scale or, for a fixed scale, a mining operation can seek to reduce costs and improve productivity.

In relation to delivering increased economies of scale, we observe that the opportunities for increasing the size of equipment are diminishing owing to the physical geometry of ore reserves. Additionally, the opportunity to engineer progressively larger mining equipment is also decreasing. This view is supported by Bartos (2007) who observed that the relatively easy financial gains from economies of scale would not be available for the mining industry in the medium to the long-term.

With this in mind, the remaining site controllable strategy is to reduce costs and improve productivity. These type of strategies to enhance NPVLOM can further be categorised into two sub-types. The first of these is often referred to as ‘sweating-the-asset’: utilising existing resources, people and equipment in a more efficient way. This is generally achieved through management intervention and monitoring, eg ensuring that shift change times are minimised for the existing workforce and the equipment operates for the most hours possible in any given 24-hour period. These productivity and efficiency interventions are the most obvious to implement once economies of scale opportunities have been exploited.

The second sub-strategy that supports the reduction of costs and improvement of productivities is through the implementation of technological innovations. However, the achievement of value through technological innovation is also not straightforward. Indeed, this is an avenue that has proven problematic at all scales of investment. Jordaan and Hendricks (2009) highlighted a number of general challenges with technology adoption within the mining industry, and Dudley and McAree (2013) highlighted five key obstacles that would need to be addressed for mining automation initiatives to be effective. These obstacles that impact on a mining operation’s ability to implement technology are real and ubiquitous across the mining sector. As noted by Hopwood and Chopra (2016), ‘despite the dizzying array of technologies available, many miners remain at the early stage of the adoption curve.’

Nevertheless, and given the limited opportunities for enhancing value through other strategies, the implementation of technological change may be the best way for a mining operation to generate increased value. For example, Durrant-Whyte et al (2015) estimated that there was $370B of value at stake for the mining industry. This value at stake could be delivered through the application of digital technologies that are either available now, or likely to be available in the near future. They identified five areas for digitisation that exist for the creation of this $370B of value. These value creation areas identified were:

1. a deeper understanding of the resource base

2. the optimisation of material and equipment flow

3. an improved ability to anticipate failures

4. increased mechanisation through automation

5. the monitoring of real-time performance to plan.

Do we need to do anything differently?

There is an argument that technological innovation is already highly progressed in the mining industry and that many of these new digital technology options will be implemented as they fulfil fit-for-purpose quality requirements for mining operations. In fact, Bladier (2016) suggested that the mining industry in Australia should be the role model for technological innovation. This perspective is complemented by the notion that implementation of technological innovations in the mining industry is difficult, compared to say, the semi-conductor industry (Bartos, 2007). This difficulty lies in unique challenges faced in the mining industry (Fisher and Schnittger, 2012). These unique challenges include, among others, geographic spread of mines, remote locations, harsh environments, access to labour, and challenging safety environments.

These highlighted challenges are further compounded by the relative, rather than absolute nature of competition between producers. This relative nature of competition is something best understood by contrasting the different positions of profitable and marginal producers to technological innovation. For profitable producers, the cost imperative does not exist to innovate technologically. In contradistinction, marginal producers often cannot afford to take the risk of innovation. This dynamic has the consequence that innovation occurs predominantly by individual choice, or in response to a competitor’s individual action.

The above mentioned points often lead to the conclusion that the industry is delivering as much as practical. Thus, there is only limited scope for enhancement of technology implementation practices. However, while it is acknowledged that there is some merit in the above points, it does not mean that there is only limited opportunity for change.

Instead, we contend quite the opposite is true. Nowadays there are fewer opportunities to achieve a lower unit cost by simply delivering economies of scale. Accordingly, the competition for a position on the lowest part of cost curve within the mining industry stands to get more complex and challenging. Rather than doing nothing, a significant technological and cost advantage awaits the producer who has the ability to navigate these unique challenges. This technological advantage will be the key to a mining operation’s future success or failure.

How can this innovation value be realised?

To what extent this technological advantage can be realised is largely dependent on the ability to understand the challenges that restrict this value from being delivered. To understand these challenges comprehensively, we are conducting a research program comprising five phases:

1. a desktop review of selected case studies

2. detailed and comprehensive review of new technology deployments, including field research and validation

3. development and categorisation of contributing factors

4. development of response strategies to mitigate these contributing factors

5. field testing of the effectiveness of these response strategies.

The paper to be presented at Iron Ore 2017 shares and summarises the work-to-date of the first stage of this research program: a desktop review of several case studies. Whilst much remains to be done, we will share our early thoughts on this problem to open discussion on how to achieve value from technological innovation.


Bartos P J, 2007. Is mining a high-tech industry? Investigations into innovation and productivity advance, Resources Policy, 32:149–158.

Bladier R, 2016. Innovation and Technology Policy, Queensland Resources Council, 2016.

Caterpillar Inc (CAT), 2016. The Journey to Autonomous Drilling [online]. Available from <http://www.cat.com/en_US/by-industry/mining/articles/journey_infographic1-download.html> [Accessed: 27 January 2017].

Dudley J J and McAree P R, 2013. Why the mining industry needs a reference architecture for automation initiatives, 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

Durrant-Whyte H, Geraghty R, Pujol F and Sellschop R, 2015. How Digital Innovation Can Improve Mining Productivity [online]. Available from <http://www. mckinsey.com/industries/metals-and-mining/our-insights/how-digital-innovation-can-improve-mining-productivity> [Accessed: 22 May 2016].

Fisher B S and Schnittger S, 2012. Autonomous and remote operation technologies in the mining industry, BAE Research Report 12.1, (BAEconomics: Kingston).

Hopwood P and Chopra R, 2016. Tracking the trends 2016: The top 10 issues mining companies will face in the coming year [online]. Available from <https://www2.deloitte.com/content/dam/Deloitte/sg/Documents/energy-resources/sea-er-tracking-the-trends-2016.pdf> [Accessed: 23 May 2016].

Jordaan J T and Hendricks C, 2009. The challenge of technology adoption and utilisation in the mining industry – a focus on open pit mining technologies, The South African Institute of Mining and Metallurgy, Base Metals Conference, pp 69–82.

Lala A, Moyo M, Rehbach S and Sellschop R, 2015. Productivity in mining operations – reversing the downward trend [online]. Available from <http://www.mckinsey.com/industries/metals-and-mining/our-insights/productivity-in-mining-operations-reversing-the-downward-trend> [Accessed: 22 May 2016].

O’Callaghan J, Burkitt J and McKenna S, 2016.
Mine 2016: Slower, lower, weaker… but not defeated, PWC [online]. Available from <http://www.pwc.com.au/publications/mine-2016.html> [Accessed:
23 January 2017].

Whittle G, 2009. Misguides Objectives that Destroy Value, Orebody Modelling and Strategic Mine Planning, pp97-101.

Share This Article