(15e) APC Sustainability and Performance Management – A New Paradigm with Integrated Adaptive Modeling Technology | AIChE

(15e) APC Sustainability and Performance Management – A New Paradigm with Integrated Adaptive Modeling Technology

Authors 

Zhao, H. - Presenter, AspenTechnology, Inc.
Turner, P. - Presenter, AspenTechnology, Inc.
Zheng, Q. - Presenter, AspenTechnology, Inc.
Campbell, J. - Presenter, AspenTechnology, Inc.


APC Sustainability and Performance Management is an ever increasing focus for refinery and petrochemical companies. This is especially true in the current economical environment where optimizing existing investments in advanced process control can pay big dividends. Changes in plant operation such as equipment aging, process and feedstock changes and ambient condition shifts will serve to deteriorate APC benefits unless the solution is maintained. In the face of operational challenges such as manpower shortages, less experienced staff, and broader scope of responsibility for engineers, efficient, effective tools are required in order to maintain the return on investment from an APC implementation.

Maintaining a controller has historically been resource intensive and traditional performance management tools have focused on data gathering and monitoring using simple calculations. Recently, more complex calculations and even online model identification have become readily available. However, the abundance of data and calculations does not improve controller performance ? rather, acting on such information does.

The new systematic approach via practical and scalable tools is designed to enable APC users to expose problems, highlight root causes, and propose remedies. Such a solution involves KPI based real-time monitoring, process change detection capability, tools for systematic problem diagnosis, and drill-down trouble-shooting. Further integration of the sustained value calculations with control and plant test software provides an automated way to generate the information-rich data necessary for the practical implementation of online analysis. Automated testing, data collection, and data slicing for use in online closed-loop subspace identification calculations provides control engineers with an extra set of hands to conduct many of the time consuming steps involved in generating an updated model. By auditing running applications to highlight problem areas before proceeding to identify replacement models, the control engineer can focus their effort on high value activities. This paper will reveal how multiple new technologies are integrated with sound control engineering practices to keep APC applications operating at peak performance.