How To Use Data To Optimize Operational Efficiency In The Metals And Energy Industries
Written by Simon Meyer
Energy, Metals & Mining
Over the past decade the mining and energy industries have experienced extensive production challenges.
Reductions in the labor force, a downturn in commodity prices, larger, more complex operations, concerns over site safety and pressure from environmentalist groups are just some of the issues the industry has been grappling with. Productivity initiatives have often been reactionary and overly focused on cost cutting, failing to encapsulate other operational areas that are essential to production efficiency. On top of this, these industries were extracting large quantities of data from their operations yet only using 1% of the information collected.
Despite the digital revolution in other industries, the mining and energy industry has been slow to embrace a digital transformation. Three core issues has stalled conversion. Firstly, the size and diverseness of the data requires extensive contextualisation before it can be utilised. Secondly, the presence and reliance on large numbers of legacy systems complicates any process of incorporation. Lastely,data administration in the past has shown to be largely insufficient and thus produces substandard data quality.
The industry is also facing another challenge. An aging workforce that doesn’t possess the required digital skills for new advancements. Marie-Helene Ben Samoun, Managing Director and Partner with BCG argues that this, coupled with the view of the industry, that it is “considered environmentally unfriendly and conservative, companies are in danger of losing fresh digital talent to other sectors”.
The current challenges for the mining industry
In a co-authored report on Value Creation in Mining, Gustavo Nieponice, Managing Director and Partner of BCG in Buenos Aires, agrees that “the talent needed to deliver on a digital strategy is in short supply” but that companies can focus on creating a digital culture, including agile practices and a ‘fail fast’ mentality, and implement digital ways of working to help acquire and develop the necessary talent and skills to succeed. “Mining companies must compete with a host of other industries and companies to attract and retain individuals who can deliver real benefits by successfully matching technology opportunities with business needs”.
“A leading drilling contractor chose agile principles when developing a new human-machine rig interface. It assembled a multidisciplinary team combining in-house designers and engineers with experts from an external IT vendor. The team, which had full decision rights, visited several rigs to understand end user needs. A product prototype was tested repeatedly in the field over eight months, with improvements made each time. The approach resulted in a 40% improvement in user acceptance, higher operating margins, lower training costs, and fewer incidents of operator error”.
The potential of using data operationally
Within the present framework, there are some companies now turning to digitisation and automation to help increase their own production efficiency. Analytics has the potential to be a far reaching tool in the production process. From machine learning to improved statistical techniques for integrating data, advances in analytics are helping to optimise complex mining tasks such as geological modelling and on-the-day scheduling. In the case of predictive analysis, improved analysis of the data gathered from equipment, vehicles, processing plants, trains and more is helping refine the prediction of failures, which is a key area of production inefficiency in the industry.
Through yielding real time responses, operations can now be optimised across the complete supply chain rather than on individual, isolated basis. Data is also having an impact on the bottom line. Analytics provides companies with the ability to evaluate the costs of the complete process. This enhances decision making and asset performance by assessing financial and non-financial indicators that have an impact on profitability. The collating of data from a wide range of distinct sources can provide on-demand reports, allow miners to improve asset operation and reliability, and reduce downtime, maintenance spending, improve safety conditions and streamline mine planning.
How data can drive innovation in the mining industry
Data technology is ever evolving and providing additional areas where data can be used to optimise production efficiency. Improvements in the affordability and accessibility of communication between machines, connectivity, analytics and mechanisation through automation are all having knock on effects. Areas such as optimising materials and equipment flow, monitoring performance in real time, transmitting data back to managers regarding hazardous conditions and understanding of the resource base in mining all now have the potential for greater efficiency.
To give an example, when mining is carried out in remote locations in potentially extreme conditions where the base of the resource is unfamiliar, accidents and equipment failures can have a serious impact on the time schedule of a production. Improved communication between already existing sensors has the potential to provide miners with a more accurate and uniform picture of the resources they are mining. This can help avoid equipment breakages against unfamiliar or unexpected material. The employment of “smart glasses” can be used to feed instructions to workers in order to carry out equipment repairs. Sensors on work clothing can connect workers to managers and transmit real time information about potential safety issues and the physical conditions of the workers themselves. The use of these technologies emphasises a central change in mining operations. The focus is now on channelling the outputted information and using smart machinery in a central capacity in order to minimise discrepancies in decision making and execution.
So far, where companies are implementing these new strategies, the results are positive. Havard Holmas, Partner and Associate Director of BCG in Oslo, notes a new pattern of working. “As a rule of thumb, we find that in successful digital transformations, companies devote 10% of their efforts to developing algorithms, 20% to building a data platform, and 70% to change management”. Holmas, who co-authored a paper with colleagues on the difficulties for mining and energy companies to go digital, goes on to note that where companies “optimize production with real time data and advanced models enabled by Industrial Internet of Things”, there is a “3 - 5 % increase in production”. They are also witnessing “20% - 40% reduced maintenance cost” as a result of “improved uptime using predictive maintenance and digital twins”.
So what does the future hold? With the dawn of Industry 4.0, Rich McKay, Content Director for IBM industries, believes companies need to be committed to utilising advances in technology to lower costs associated with maintenance and extraction. “It is clear that the use of advanced analytics and AI helps optimise production processes. When factories are instrumented through the IoT, available data surges. In a digital factory, operators can use data insights to identify potential production losses and act to balance quality, cost and throughput. The result? Fewer disruptions, less waste and higher yield”.
Creating the right mindset and driving impact
Nevertheless, a report from PwC states that “compared with many other industries, mining’s level of technological maturity is still relatively low. Only seven of the Top 40 have a Chief Technology Officer, Chief Information Officer or Chief Digital Officer in their senior management team”. Despite PwC’s report in 2018 that “companies who achieve digital technology mastery earn higher revenues and lower their costs consistently over time”, investment in technology appears to be stopping upstream.
There is now a significant opportunity to apply the research and innovation to all aspects of the industry. Changing mindsets to think about technology in connection with the whole supply chain will start to create a culture of innovation, which can only have a positive impact on production efficiency. For companies change can happen in three clear steps. “First, put digital to work to transform the core of the business. Second, find new offerings that can be built through digital. And third, enable teams so that they can execute digital strategies effectively over the long term”.