Pavilion8

Complex industrial processes make it challenging to be both market driven and sustain profitable operations. Manufacturers must adjust their production methodology to introduce a greater variety of higher value products and shorter production runs. They need to produce more, run efficiently and improve product quality to the limits of available equipment. For this, they must ensure maximum uptime and more efficient transitions with less waste. In addition, manufacturers are facing stronger public demand to reduce their environmental impact and operate within regulated emissions limits.

Rockwell Automation Pavilion8® Model Predictive Control (MPC) technology is an intelligence layer on top of automation systems that continuously drives the plant to achieve multiple business objectives—cost reductions, decreased emissions, consistent quality and production increases—in real time. Pavilion8's flexible hybrid modeling capabilities incorporates all available process knowledge to deliver the most accurate, highest fidelity models possible. It uniquely provides a single solution that can handle both nonlinear and linear processes simultaneously, driving improved results across a wide range of process technologies. Our MPC technology continuously assesses current and predicted operational data, compares them to desired results, and drives new control targets to reduce process variability, operate within equipment constraints and improve performance.

Greater Model Accuracy

Pavilion8 offers hybrid modeling based on empirical data, first principles equations, operator knowledge or using any combination thereof. Soft Sensors® can integrate with Pavilion8 providing timely in-process measurements to increase accuracy of control actions. In addition, our patented Extrapolated Gain Constrained Neural Networks (EGCNN) ensure model accuracy beyond the historic operating ranges. All this expedites deployment, minimizes need to adjust models as process range is extended, and maximizes value delivered.

Tighter Operational Control

The solution incorporates changing process dynamics over wide process operating ranges. Its parametric model representation provides compact, computationally efficient controller model without sacrificing accuracy. This improves plant performance across wider operating regions, provides tighter operating range control, and significantly increases flexibility across changing grades including more rapid new product introduction.

Higher Controller Performance

You can maintain a contextual history of control actions and improve troubleshooting via controller replay capability. The embedded controller performance metrics track and present performance enabling accelerated, effective sustainability. This allows quick identification and resolution of model mismatch or tuning parameter errors for improved controller performance. It also helps achieves predictable, sustainable performance through continuous controller monitoring.