It Takes Two....

Here’s How Three Users Learned the Steps to Prioritizing Process Data to Secure Useful Measures to Improve their Operations

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To better manage the cracker’s close to 1,000 control loops, Mikko Rönkä, Borealis’ automation engineer, reports his company adopted three upgrade strategies: train operators with a simulator, revise its APCs, and improve its regulatory controls with ExperTune’s PlantTriage software. “The software connects to the control system via OPC and then identifies and prioritizes opportunities to improve regulatory control,” explains Rönkä. “The software allowed us to see, for the first time, the performance of all the important control loops in our plant, and we uncovered a host of control system opportunities.”

Presentation Priorities

While accurate numbers and precise calculations are the heart of data collection and optimization, the way in which meaningful information is presented also is gaining importance. To quickly view and respond to their own loops, Borealis’ engineers and operators check PlantTriage’s dashboard displays and use its “Biggest Payback Loops” list, which shows specific loop details and likely root causes.

“Temperature controls used to be notoriously difficult in the ethylene facility. Previous manual attempts left us with controls that worked, but weren’t optimal, but PlantTriage’s integrated tuning and loop-optimization tools let us push closer to optimal,” adds Rönkä (Figure 2). “The robust controller tuning eliminated loop cycling and interactions, which added stability to the process, and allowed us to use APC. We also focused on the control valve, because it’s the most likely point of failure in a loop. Using valve-travel diagnostics, we identified control valves with the most wear. The root cause usually is related to tuning or inadequate instrument signal filters, and can be addressed easily.”

Borealis Polymers Oy’s ethylene cracker
Figure 2. Repaired valves and better loop tuning provided more optimal control of temperature and other process variables and improved performance of Borealis Polymers Oy’s ethylene cracker in Porvoo, Finland.

Ramping Up to Real Time

Besides being archived out of reach, data in traditional historians often are accessed too late to aid their processes. Sure, they can provide some after-the-fact indicators and trends, but today’s applications require intelligence much closer to real time, so they can make corrections as production occurs.    

For instance, Sasol’s Infrachem Utilities and Syngas division recently collaborated with Invensys Business Performance Services to improve operations at two steam plants at its Sasol One facility in Sasolburg, South Africa. Sasol and Invensys developed dynamic performance measures (DPMs) to provide underlying real-time performance measures for each of its steam production units, and also deployed real-time financial metrics to calculate cost and profit for each process unit and area. Next, they  staff created management and operator dashboards that use the DPMs and financial data to give managers real-time information so they can make better-informed decisions.

These DPMs bring together accounting, engineering, management, operations and maintenance to discuss Sasol’s overall business. Sasol and Invensys report that this interdepartmental interaction creates understanding across business functions, helps develop strategic performance measures across those functions and creates new business processes for improving the bottom line.

In the first month after the DPMs were installed and gained more consistent fuel oil use and boiler tuning, Sasol saved 6% on its energy feedstocks and 4% on electricity costs for making steam at Stations 1 and 2, and these results improved over the next two months. Overall, Sasol Infrachem and Invensys are saving more than the $400,000 per year they expected to from Sasol One’s two steam plants, and the partners are now rolling out their real-time performance measures at five other plants. Bow to your partner. 

Jim Montague is Control’s executive editor.

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