Advanced Analytics Helps a Mining Company Improve Quality and Reduce Costs

At one of the sites that a global mining company operates, contaminants were making their way into roughly 20% of the products, decreasing production capacity and driving up reprocessing costs. In addition to the cost impact, MiningCo believed that mitigating these quality issues would help it gain market share relative to competitors.

In close collaboration with process engineers, we trained an algorithm to find the key factors that determine “good” and “bad” product batches based on more than 250 variables from across a range of data sources at every step of the production process. We used the results to identify the root causes of poor quality and ways to mitigate it through some precise interventions.

With our help, MiningCo established an ideal process operating envelope and made several adjustments to its preventative maintenance plan for certain equipment. Other changes to the mine’s operations included a new process control loop with an alarm to signal a deviation from the targeted operating envelope.

As a result, contaminants and related defects in the site’s products dropped by more than half, and MiningCo increased the plant’s overall equipment effectiveness by more than 10%. The cost savings gave the company an EBITDA uplift of roughly 10% to 20%.