October 2022

Digital Technologies

Data, algorithms and collaboration combine for machine-learning success

Process manufacturers are investing significant resources in machine-learning (ML) to increase reliability, profitability and sustainability in their operations—saving millions of dollars in short periods of time through increased efficiency.

Venkat, A., Zakeri, S., Disantis, J., Seeq; Johnstone, A., Ithaca Energy; Martin, J., allnex

Process manufacturers are investing significant resources in machine-learning (ML) to increase reliability, profitability and sustainability in their operations—saving millions of dollars in short periods of time through increased efficiency. As interest in ML grows, focus is rightfully placed on developing and enhancing the associated algorithms, but manufacturers must examine the results of these algorithms to ensure that ML efforts are successful. This is because operationalization of algorithms, not an algorithm itself, is the linchpin to providing meaningful value. Successfully applying ML in an industrial setting requires participation from engineers and other plant operations personn

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