Case in point.

EFT partnered with a Flint Hills Resources facility to use machine learning within a propylene facility to identify optimal operational settings that increase production (within permitted limits) and decrease emissions.

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EFT applied CORTEX to pinpoint issues with an industrial compressor. Using historical data, a leak in one of the inter-stage coolers was identified quickly to avoid unplanned downtime.

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EFT partnered with Big River Steel to deliver a solution around the industry-wide problem of strip breaks. Using Big River’s data, EFT pinpointed an equipment issue and then determined the optimal set points that produced the strongest weld.

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A manufacturer was experiencing unexplained declines in product quality. EFT improved production by delivering an event notification dashboard interface that created alerts when yield was expected to drop.

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A machine would frequently break when pushing additional throughput – resulting in $1M/month loss. EFT Analytics found a weekly anomaly causing significant breaks saving the facility $12M in wasted production.

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Quality issues within a facility, Big River Steel, were not detected until after the material had been processed and were often inexplicable in operations. After helping identify key variables tied to these defects, EFT compiled data from multiple sources to predict these quality issues in real time.

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By starting with 700 data points hourly, EFT identified why this facility’s production significantly dropped over four years. The model EFT created is providing a better solution for the site while also providing the conditions needed to increase overall production.

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Previous pre-flaring event notification time for a facility was just five minutes. Using existing sensor data, EFT helped deliver 40+ minute notification time and assisted in increasing overall profit while reducing environmental impact for the facility.

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EFT delivered a summary report identifying variables and variable ranges to improve knockout percentage in a partial condenser unit, resulting in roughly $1M in annual savings. A live dashboard was deployed to further optimize their process in real time.

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A facility was experiencing multiple power boiler plugging incidents annually, costing them $18M per event. EFT identified and provided a model that gave them days to weeks advanced notice – allowing them to shut down without incident.

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