What the mining and metals industry can gain from predictive analytics

Fernanda Martins Process Industries Expert AVEVA 1Safety and reliability are more important than ever in the mining and metals sector. As organisations look to digital transformation for optimising operations and maintenance, they are discovering the benefits of combining operational data management with predictive analytics, says Fernanda Martins, process industries expert, AVEVA

Mining and metals companies are facing a growing array of challenges, from volatile markets and tougher competition through to regulatory compliance and decarbonisation. 

In fact, environmental, social and governance (ESG) objectives are the number one priority for miners in 2022, according to a survey by Ernst & Young (EY). At the same time, industry leaders are having to deal with dwindling resources, deeper mines, rising energy costs and infrastructure shortages, which are all putting them under extreme pressure to improve efficiency and cut costs. 

How to face disruptive times in the metal and mining industry 

There might not be a quick fix, but technology has a key role to play in improving the performance, reliability and efficiency of mining and metal operations going forward while keeping on track of the ESG targets.

Covid-19, for example, highlighted the potential of digitalisation to improve health and safety onsite. According to EY, miners that were already using automation and remote operating centers (ROCs) fared better during the pandemic, and the organisation expects to see investments in this technology grow during 2022. 

Mining and metal companies are also deploying technology as part of their ESG agendas, as digital innovation can support strategies to minimise the consumption of natural resources like water, reduce waste and improve transparency of reporting.

Technological innovation, and in particular artificial intelligence (AI), is helping the sector in a wide variety of ways, from supporting the discovery of more financially viable mineral deposits through to optimising operations. But there’s one area in particular that’s unlocking a wealth of actionable insights for mining and metal businesses, and that’s predictive analytics. 

Unlock valuable operational insights

A modern mining organisation produces masses of data every day. Hidden in all this information are valuable insights that have the potential to help reduce unplanned downtime, streamline processes, improve asset performance and achieve more reliable and predictable outcomes.

A predictive analytics solution turns raw data into actionable insights that can help diagnose equipment issues days, weeks or even months before failure. Predictive analytics models combined with a deep learning approach can even forecast an asset’s remaining useful life.

Mining company Barrick Gold, for example, was able to reduce environmental-permit deviations by 45% after getting access to actionable digital insights that allowed it to adjust operations in time to ensure environmental compliance.

Transition to predictive maintenance 

This technology enables organisations to transition to predictive maintenance, which minimises downtime and disruptions and can optimise maintenance schedules. 

Advanced statistical and model-based comparison applications and business intelligence (BI) tools enable users to spend less time searching for potential problems, with alerts providing early warning indications of when an asset’s current operation deviates from the norm.

Advanced predictive analytics solutions also include the ability to provide users with prescriptive action to mitigate a potential failure and optimise the maintenance strategy. 

These can empower the workforce to execute predefined guidance when addressing asset maintenance and performance issues, resulting in improved decision-making and consistency in how issues are investigated, managed and resolved. 

Predictive analytics offers substantial time and cost savings

According to Deloitte, moving from a reactive, condition-based maintenance strategy to a more data-driven proactive approach can offer big savings. It has estimated that predictive maintenance can reduce mining and metal operations’ maintenance planning time by 20-50% and overall maintenance costs by 5-10%.

We’ve seen it save millions in averted asset failures – Syncrude Canada, for example, saved US$20mn in annual operating cost avoidance, while another major mining and metal company saved US$17mn from avoided unplanned downtime. 

Another example comes from Votorantim Cimentos, Brazil’s largest cement manufacturer. It introduced a predictive analytics solution in order to reduce the overall cost of maintenance, increase productivity and enhance operational reliability.

Across six initial sites, predictive analysis-driven catches avoided US$5.5mn in corrective maintenance costs per site. 

In the first year alone, savings totaled US$88mn and between 2019-2021 the company saw a 10% reduction in maintenance costs and a 6% improvement in asset reliability. This virtually eliminated the need for any emergency maintenance purchases. 

“We wanted to realise a vision of our next generation plant operations, using data to shape our decision-making. We were able to see benefits within weeks, driving unparalleled optimisations that spanned our entire operations and network of plants,” said Fabio Eduardo Scarlassari, global maintenance general manager at Votorantim Cimentos. 

“At its heart, digital transformation is about people being able to embrace new ways of working and truly becoming data-led experts in all that they do. [With this solution] we were able to make that shift in our thinking and the benefits for our team have been truly transformational. 

“We have elevated our performance and now we can operate with greater efficiency and operational agility than ever before.”

More valuable insights, more reliable operations 

Predictive analytics empowers maintenance planners, systems engineers, controllers and other mine personnel to make real-time decisions that improve performance, reliability and the bottom line. 

It is important to note that leading predictive analytics solutions do not require a data scientist to model and configure the application. The latest technology is easy to implement and has quick payback.

This can help mining and metal organisations not only to face today’s challenges head on, but also work towards their ESG goals by achieving better asset and process outcomes that minimise energy use. 

To learn about the benefits of predictive analytics and how AVEVA transforms the mining industry, click here

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