Corteva Uses Hybrid Models for More Accurate Predictions and Improved Maintenance

In this case study, learn how Corteva Agriscience, an American agricultural chemical and seed company, resolved their frequent reboiler shutdowns by using Aspen Hybrid Models™. By combining plant data and AI within an Aspen Plus® model, Corteva improved the heat transfer and duty predictions to provide guidance for a better maintenance strategy.

The hybrid model, created in less than a day, provided guidance to:

Prevent unscheduled shutdowns, potentially saving $1.2M USD/year in avoided maintenance costs and nearly $10M USD/year in avoided product sales losses
Improve maintenance shutdown schedule
Lower tar levels for smoother operation of upstream solvent distillation columns
Take a proactive maintenance approach towards exchanger cleaning and tar purging

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Asset Performance Management

Digital Grid Management

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Corteva Uses Hybrid Models for More Accurate Predictions and Improved Maintenance

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