Modern Model Predictive Control (MPC) methods were first developed in the petroleum refining industry in the early 1990’s. MPC creates a computerized cruise control system for your plant that attempts to match or exceed the performance of your best operator. Although petrochemical and refining are a core segment of our business, our model predictive control successes include ethanol plants, air separation, polymerization, batch, and mining and metallurgy

Soft sensors are a key technology in modern process control. The objective is to use readily available signals such as temperature and pressure to infer an intermittently measured value such as a lab quality test. Although predicting lab results is a common application, the same technology can be used to predict future process values, instrument errors, or imminent equipment failures. Our technology allows users to define several modeling approaches such as time series, state space, Kalman filters, neural networks etc. and the technology will automatically select the most reliable method for a particular operating regime.