‘Big Data’ will drive sustainable mining productivity – Deloitte

The automation of operational data collection and delivery will enable mining operators to make informed, real- time decisions concerning daily mining operations, as well as improve safety.

“Operational intelligence is driving fundamental changes in the way information is exploited in mining,” says Deloitte Partner Links Chithiray in a new report. “These solutions are delivering new insights to mine site executives, management teams and operations staff that reflect their environment and empowers them to make data-driven decisions on performance and cost.”

“Ultimately, the goal of any mining operation in simple terms, is to optimize production at the lowest cost with zero harm to the workers and the environment,” he observed. “It is no coincidence that despite the tougher market conditions, global mining leaders are making big data investments in operational intelligence, remote operations centers, automation, analytics and mobility.”

The Deloitte report, Extracting business value through operational intelligence, asserts that mining operational efficiencies may be gained by automating and integrating information across the value chain, which can also inform the more radical step of redesigning mining operations.

“CEOs of leading global mining companies are already investing in capabilities by analyzing large volumes of data in real time to improve production, quality and equipment efficiency where they are seeing the benefits now,” said the report. “Operators at remote sites and executives in head office can be presented with the same data, in tailored formats and at the right frequency for all parties to make more responsive and fact-based decisions.”

Usually large, geographically dispersed mining organizations tend to use different reporting and analytical solutions while working off different data sources often with “subtly different data definitions”, Deloitte observed. “However, for operational intelligence to be a true lever of operational efficiency, management teams and operators should be working off the same underlying information and consistent data definitions.”

“For example, the data on real-time equipment performance used by an operator, when aggregated across sites and time periods, is useful for conducting comparative analysis, benchmarking studies and identifying operational improvement opportunities,” said the report.

Through utilizing a large screen visualization of performance for the ‘pit-to-port’ processes within remotely located operational nerve centers, one mining CEO observed, “For the first time we can see our total supply chain, in real-time and in one place, enabling us to proactively make the right decisions for the whole business.”

Among the challenges of integrating operational intelligence are: getting agreement on what needs to be measured in the operations environment; data quality and integration; and a reluctance to expose operational data before it has been validated.


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