How CLPM Can Optimize Throughout a Lifecycle of Optimization

It may be helpful for production staff to view optimization as it really is: A never-ending project. Indeed, there is no fixed finish line. Those assigned to optimization need to accept that once new benchmarks are achieved those new standards now need to be maintained if not improved upon. Fortunately, control loop performance monitoring (CLPM) solutions and other analytical tools have gained market traction, and those tools are helping staff to optimize throughout a lifecycle of optimization.

Optimization is different for most every manufacturer and even every production facility. Performance challenges and goals for optimization can be expected to vary depending on the plant, the processes, and the people. As an optimization initiative transitions thru its different phases, technologies like CLPM can provide project staff with the tools needed to steadily raise the bar and advance production control to the next phase of maturity.

Consider how CLPM can be applied at each of the following three phases:

The Optimization Newbie

Getting started can seem like the most difficult stage of an optimization initiative. Manufacturers may not have all of the resources they need, and they may be hesitant to take that first step.

There are a number of obstacles that any manufacturer will need to overcome in order to effectively pursue optimization. For sure, breaking old habits and embracing new approaches is difficult. Starting small and picking off low-hanging fruit can be the key to a successful launch. As with most things in life: Success breeds success. To that end CLPM vendors typically emphasize a focus on running as many controllers in automatic as possible and moving away from manual control.

Percent Time in Normal (PTIN) Mode is a simple key performance index (KPI) included with most CLPM solutions. PTIN Mode indicates the length of time that a PID control loop is operated in its ‘normal’ state – whether that state is Automatic, Cascade, or something else. It’s common for manufacturers who are embarking on optimization to have a sizable portion of their controllers in manual. Meaningful performance gains and the start of an effective optimization journey can be realized simply by transitioning those control loops to an appropriate automated mode.

The Well-On-Their-Way Optimizer

Manufacturers who have been engaged in optimization for a period of time can run the risk of becoming frustrated. With many of the easy targets achieved, maintaining momentum can present a challenge.

Manufacturers can lose ground just as easily as they gained it. While easy wins may have provided excitement and demonstrated the value of optimization, finding an appropriate path forward and sustaining an optimization initiative requires commitment. With no more low-hanging fruit it’s necessary to reach higher, and for many manufacturers that next step involves adjustments to the many final control elements (FCEs) that help to regulate control and even the facility’s control strategy. In order to identify underperforming FCEs such as valves and dampers, CLPM solutions rely on KPIs like Output Distribution and Output Travel.

Whereas the first KPI calculates the distribution of a given FCE’s position during closed-loop operation the second KPI calculates the amount of effort applied toward maintaining control. Essentially, Output Distribution informs staff when a FCE (e.g., valve, damper or pump) is sized incorrectly – whether too large or too small – and Output Travel pinpoints FCEs that exhibit excessive movement and that are on course for premature failure. Correcting these issues takes time and effort. However, the impact on plant performance can be meaningful, and the resulting progress can help to sustain an optimization initiative.

The Old-Hand Optimizer

A culture that supports the goals and the grind of optimization is the hallmark of efficient, profitable manufacturing. Getting to that level isn’t easy. Finding new way to remain at the level isn’t easy either.

Optimization can be a grind particularly for manufacturers at the mature stage of the optimization lifecycle. For sure, all of the easy adjustments for improving control have been implemented so nothing is easy. Even so, with a culture that embraces continuous improvement and access to the right tools, incremental gains are achievable. For manufacturers equipped with a CLPM solution, Average Absolute Error (AAE) is a KPI that can be leveraged to continue along the optimization journey.

AAE quantifies the difference between a PID loop’s Set Point and the corresponding measured Process Variable. Essentially AAE provides a simple measure for tracking how effective a loop is at maintaining Set Point. More specifically, AAE assesses change in the loop’s performance whether that change is big or small, and it provides production staff with the clues needed to continue with their optimization initiative. Until there’s no Error left to eliminate, the job of optimization is never done.

Optimization is a continuous journey with no specific end goal, and it is challenging. Fortunately, CLPM solutions like Control Station’s PlantESP provide intuitive tools for both identifying and resolving performance issues throughout the optimization lifecycle.

These resources offer related content:


What Role Should CLPM Play in a Process Manufacturer’s Intelligent Operations Strategy? How Does CLPM Contribute to Improved Process Health and Asset Health?

PID control loops are critical in the regulation of plant-floor production processes. The health of these loops serves as an indicator of the wellness of a facility’s overall production process and its ability to operate efficiently. This suggests that investing in control loop performance monitoring...

Why is Zeigler-Nichols the Wrong Choice for Your PID Controllers?

PID Control Loops Have Specific Purposes and Unique Attributes.  'One Size Fits All' Approaches to Tuning May Be a Recipe for Failure.    In 1909 Henry Ford famously offered customers any color of his Model T automobile as long as their choice was black. Ford's...

Common Industrial Applications of PID Control

  PID Control May Struggle With Noise But There are Numerous Applications Where It's the Perfect Fit. A previous post about the Derivative Term focused on its weaknesses. As noted, the primary challenge associated with the use of Derivative and PID Control is the volatility...

Still looking for more?

Now that you’ve gotten the basics, connect with our team to learn how our people, processes and technologies can help you optimize.