Perhaps the most common application of machine learning in the process industries is to support predictive maintenance. Anomaly detection is widely used to identify equipment performance degradation much earlier than using traditional condition monitoring systems and data analytics. However, the use of artificial intelligence to improve reliability and reduce maintenance costs is still in its infancy.
Read moreAutonomous Operation
The ultimate goal of automation is autonomous operation. Autonomous operation requires plants that operate without human intervention and continuously adapt to changes in their environment.
Read moreDriving innovation and enterprise resilience
If there’s anything positive to take away from the COVID-19 situation, it’s that it forces innovation and enterprise resilience.
Read moreDisruption of value chain optimization
Value chain optimization involves the agile and efficient alignment of supply of premium products as closely as possible to market demand with sufficient resilience or operational flexibility to readily adjust production and exploit market opportunities.
Read moreData Integration and Knowledge Management in the Process Industry
Digital systems were first widely implemented in the process industries in the 1970`s. Since then there has been a sea of process data and a proliferation of databases and many attempts to integrate them using data warehouses, middleware and web services. Most of these attempts have had limited success and are difficult to maintain and scale.
Read moreRefinery Optimization in the age of AI
Combining multivariable predictive control, simulation and artificial intelligence to optimize refineries and petrochemical plants.
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