aspenONE® Advanced Process Control for Specialty Chemicals
Enables consistent and safe manufacturing performance; maximizes operational agility and profitability
aspenONE Advanced Process Control for Specialty Chemicals enables manufacturers
to optimize production operations, providing greater agility in responding to market
demands. The solution set enables process and product consistency by minimizing
variability and facilitating consistent manufacturing execution with a solution
that features both commercial and technical scalability. Companies deploying aspenONE
Advanced Process Control for Specialty Chemicals realize significant improvements
in performance and profitability. Benefits include increases in yield, reduction
in quality variability, increases in throughput, and reduction in off-spec material
losses.
aspenONE Advanced Process Control for Specialty Chemicals is comprised of the
following:
- Aspen Process Controller is the fully configurable model-based
controller engine used to keep the process at optimally determined set points. Users
can choose between three industry-leading control formulations including both linear
and non-linear approaches. The easy-to-use graphical interface allows operators
to visualize all key process operations in a single screen and efficiently manage
and interact with the controller.
- Aspen Inferential Qualities enables modeling and implementation
of inferred product qualities, and makes it possible to implement linear or non-linear
inferential sensors on-line. Inferential sensors are fundamental elements of many
advanced process control systems. Key parameters (such as naphtha 95% point and
polymer melt index) are often inferred rather than directly measured.
- Aspen Performance Monitor provides built-in controller KPIs along
with the ability to define and implement KPIs for loop and process monitoring. Aspen
Performance Monitor provides drill-down capabilities to quickly identify the source
of eroding performance and corrective action features that automate step testing,
data pre-processing, and new model identification.