08 Nov Back to basics: Regulatory Control Optimisation
The basics done well + ruthless consistency = high performance. A simple formula for success, often overlooked.
In the context of running a process plant, effective maintenance of PID loops falls squarely into the category of getting the basics done well. PID is the dominant regulatory control solution used across the process industries; an effective regulatory control optimisation strategy provides the foundation for maximising safety, reliability, and profitability.
Regular tuning of a plant’s PID controllers is a proven way to improve process performance and increase plant profitability substantially. Despite this, our experience has shown that many companies consistently overlook the performance of PID loops as a route to increasing profitability. It has been estimated that 80% of process control loops cause more variability when they are run in automatic mode than when they are run in manual mode. About 30% of all loops oscillate due to non-linearities such as hysteresis, stiction, deadband, and non-linear process gain. Another 30% oscillate because of poor controller tuning.1
Plant performance studies have shown that the largest opportunity for reducing costs lies in improving field device performance and loop tuning. The below chart shows the savings associated with different process control categories (Brisk, 2004)2. The savings are expressed as a percentage of production costs.
How Control Loop Performance Monitoring solutions can help
With a typical process plant consisting of 100s if not 1000s of PID control loops, monitoring each to ensure best performance is a genuine and significant challenge. Thankfully, technologies that continuously monitor control loop performance and identify issues that may negatively affect production can help with this onerous task. An effective CLPM solution will include:
♦ Capability to find underperforming PID loops and automatically prioritize them, highlighting those that require immediate attention.
♦ Supporting visual tools that can be used to diagnose the most likely causes of the degraded performance.
♦ A data historian capability to collect, monitor and visualise PID loop data for control loop performance analysis.
♦ Advanced data analytics and performance metrics that can be used by a control engineer to monitor loop performance.
♦ Tools for model identification and PID loop tuning parameter optimisation.
PID controllers are integral to maintaining safe, reliable and profitable control of a manufacturing plant. Appropriate steps need to be taken to monitor and continuously adapt PID control loops to changing conditions. CLPM technology can be viewed as a relatively simple, yet extremely effective way for manufacturers to substantially increase plant profitability.
MPC and CLPM as complementary technologies
Establishing a “good foundation” of the basic regulatory control loops is essential to the success of higher-level Model Predictive Control applications.
At Spiro Control we have extensive experience of implementing large-scale MPC applications. In each implementation we oversee, a crucial first phase of the project involves verifying the proper functioning of all essential instrumentation and regulatory controls. All PID loops are tested and tuned, and any faulty transmitters or analysers, sticking valves or similar issues identified. In this phase, the objective is to establish the “good foundation” necessary for a successful MPC implementation.
As well as helping in commissioning of an MPC application, a plant using an effective CLPM solution to maintain well performing PID loops can expect an MPC application to sustain high performance for longer.
To find out about the unique benefits delivered by Spiro Control’s CLMP tool visit http://www.spirocontrol.com/spiro-pid/. If you have any comments on this article or are interested in finding out more, we would love to talk with you. You can reach us at firstname.lastname@example.org.
2 M. L. Brisk, “Process Control: Potential Benefits and Wasted Opportunities”, in 5th Asian Control Conference, vol. 1, 2004, pp.20-23