Freeport-McMoRan‘s patent involves a method using historical and future data to predict mining production targets. By analyzing deviations between forecast and actual data, parameters affecting production are identified. The processor can activate deep raffinate injection based on the analysis to address potential issues like unleached copper in stockpiles. GlobalData’s report on Freeport-McMoRan gives a 360-degree view of the company including its patenting strategy. Buy the report here.

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According to GlobalData’s company profile on Freeport-McMoRan, Extraction by leaching was a key innovation area identified from patents. Freeport-McMoRan's grant share as of March 2024 was 67%. Grant share is based on the ratio of number of grants to total number of patents.

Predictive model for mining production target with leaching operations

Source: United States Patent and Trademark Office (USPTO). Credit: Freeport-McMoRan Inc

A recently granted patent (Publication Number: US11948103B2) discloses a method for optimizing mining production through the use of sensor data and predictive modeling. The method involves acquiring data from sensors monitoring mining production, identifying deviations between forecasted and actual production data, determining the factors contributing to these deviations, and specifically targeting areas with potential unleached copper in stockpiles. By activating deep raffinate injection in these areas, the method aims to improve overall production efficiency.

Furthermore, the method includes training a predictive model with historical data, conducting leaching operations to gather data, validating the model with test data, and incorporating future assumption data based on mine plans. By running a forecast engine for various parameters, the method enables mining operations to proactively address issues such as unleached copper in stockpiles, ultimately enhancing production outcomes and efficiency in the mining industry.

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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.