“Using Tai-Ji to step test the plant in a closed loop mode was great,” says Mike Golinsky, ROC engineer for BOC. “It reduced testing time, improved model quality and, most importantly, reduced the risk of a loss-producing event occurring during the testing process.”
While the step test was underway, we conducted modeling passes every 12 to 16 hours to give the implementation team direct feedback on how the test was going. This feedback led to step size changes to the CV targets (higher signal-to-noise ratio) to better develop the models. Toward the end of the step test a lot of key models had converged — so, the decision was made to put them online with the step test still going on. With the new models online and the step test running, commissioning of the new models began. This is the new methodology at its peak, with all four phases — integration, step testing, modeling and commissioning — occurring at the same time. Once the step test was over, commissioning and fine-tuning of the plant continued.
The end result of using this methodology was the commissioning of a reliable grassroots MPC in 12 work weeks rather than the industry standard 3-4 months (Figure 1). The greatest challenge faced in this implementation was neither technical nor operational — it was achieving confidence in the results of the new method. After all, it’s so much easier to see results when step testing is done one MV at a time versus moving all MV together. BOC had a tough time in the beginning believing the results from Tai Ji but eventually confidence grew and it accepted the results.
Figure 1. Overlapping of phases in Tai Ji method significantly shortens implementation time.
Even then there was a challenge in getting operations staff, conditioned by five years working with an under-performing MPC, to trust the new controller. The operators were so accustomed to seeing issues with the old MPC that during the step testing and commissioning phases they always were quick to jump in to take a loop out of MPC and put it into automatic.
Asked why a certain action was taken, an operator replied, “Well, the old MPC would tend to bury this purity, so I don’t want to take any chances and have an upset.” An upset could mean anywhere from four to eight hours of lost production. It took a while but the operators finally developed enough confidence in the new MPC.
Immediate benefits and future plans
When you add up the savings in engineering coverage, operator interventions and time necessary both for testing and analyzing data — all cut by approximately 50% — the real bottom-line benefit of implementing an MPC in this compressed time frame is enormous. This is in addition to the well-known industry-proven advantages of having a reliable well-modeled MPC. The Hartford site gained a number of important benefits:
- increased LPC stability, which leads to better CLAR recovery, reduced operator intervention, and less downtime or fewer loss-producing events;
- the ability to change production rates very quickly, without upsetting the plant and the key purities;
- optimization of the evaporation tower;
- improved control of power demand — the MPC is set up such that it can drive production while also maintaining the power demand targets set by the power company;
- better load-following on pipelines — the MPC can quickly adjust plant production to meet changes in pipeline demand;
- enhanced constraint handling; and
- improved ramping — overall average ramp rate improvement of 220 to 650%.
“LMPC [Linear Model Predictive Control] has done a much better job than our previous APC [Advanced Process Control] system in maintaining the ever-so-critical low pressure column purity control,” says Golinsky. “The LMPC system has been in place five months now, and our downtime on argon has been reduced by over 75%. The plant will run for weeks or longer without operator intervention being necessary on the LPC purity.”
The old underperforming MPC didn’t provide any of these benefits. While specific numbers for the Hartford plant aren’t yet available, Golinsky estimates a $20,000/year savings from reduction in upsets alone. Industry experience shows that a solid MPC implementation will provide $80,000 to $85,000 annual benefit to a plant.
After the demonstrated success at Hartford, BOC is implementing this methodology at other eight plants. We have finished two already and are currently are in the process of doing three more.
Zul Bandali is an advanced controls engineer for Matrikon in Edmonton, Alberta. Reach him via e-mail at Zul.firstname.lastname@example.org