Drilling down on a specific loop can help confirm the diagnostics. Notice the large repeatable swing of the process variable in Figure 3.
Valve Travel. The control valve is the control system’s workhorse. Valve travel is a good overall indicator of maintenance demand and loop performance. It’s calculated by summing the amount of valve travel over a day. Each time the control valve moves up or down, we can totalize the amount of movement and learn something about the controller and the valve.
Excessive movement of a control valve creates two problems:
• inordinate wear on the valve; and
• process upsets induced by the extra valve movement.
When a performance supervision system is first installed, you can find some major problems very quickly by looking first at the extent of valve travel.
Other Performance Metrics. Some more-sophisticated measurements can help pinpoint specific process issues. A few examples include:
• Oscillation detection and oscillation periods allow you to find the cause of routine process upsets.
• Comparisons with process specification limits enable operators to push the process closer to optimal operation.
• Interaction maps, such as the one shown in Figure 4, establish cause-and-effect relationships within the plant.
Sometimes looking at metrics together can tell you something more about the process or equipment. For example, when the maximum value of the PV over some time period equals the minimum value, then the instrument has “flatlined” or failed. This is a common mode of failure for many types of instruments including thermocouples and level transmitters. Many plants continue running for days or even months without recognizing that some instruments have failed in this way. Yet a simple diagnostic comparison like this will lead your instrument technicians directly to failed instruments.
Improving Control System Performance
You can’t control what you don’t measure. Start by measuring some simple statistics for your control system. With “Time in Normal,” “Time at Limits,” and a few other metrics, you’re on the way to discovering the key limitations of your process.
Measure the right things. You easily can get side-tracked by calculating hundreds of meaningless metrics. Make sure that you’re measuring those things with the greatest impact on the bottom line. For example, if your business wants increased production rates, then you should monitor valves at limit. But if the focus is on energy reduction, then a better place to start might be oscillations in temperature loops. Always ensure that you can establish a link between the business goal and the metrics you’re using.
Prioritize. Use both economic and technical data to focus efforts. Does it matter if the waste processing surge tank has wild variations? Probably not. Concentrate on processes and controllers that impact key parts of the business. Make sure you have a way to identify which control loops affect the bottom line and which ones don’t.
Take focused action. Software alone doesn’t make the plant run better. You must take action. The metrics will show you where to take action but it’s up to you to ensure action is taken. Use a spreadsheet to track all actions needed, including valve repairs, instrument calibrations, loop tuning and control strategy changes. Assign responsibilities and deadlines for each item — then follow up to ensure they get done.
Track and report results. Putting results in business terms is a weak spot for most engineers. However, always make an effort to track and report your results in such terms. For example, if you’ve reduced variability by 50%, has this resulted in fewer rejects or less recycled product? It’s usually much easier to assign monetary value to a reduction in rejects than to generic “variability reduction.”
Once you have some bottom-line benefits, broadcast your success. Make sure that operations managers know. They may have other processes that need the same type of improvement.
George Buckbee, P.E., is director of product development at ExperTune, Inc., Hartland, Wis. E-mail him at firstname.lastname@example.org.
1. Ronka, M. and G. Buckbee, “Control Performance Supervision Enhances Revamp,” Chemical Processing, April 2008, www.ChemicalProcessing.com/articles/2008/052.html.
2. Boyes, W. and G. Buckbee, “Why do you Need Performance Supervision,” Control, April 2006, www.ControlGlobal.com/articles/2006/070.html.
3. Brisk, M. L., “Process Control: Potential Benefits and Wasted Opportunities,” 5th Asian Control Conference, Melbourne, Australia (July 2004).