Introduction

Process plants already have modern control systems in place, utilizing PIDs to regulate flows, temperatures, pressures, and levels across the plant environment. Yet despite significant investment in automation, manual operation, excessive variability, and mechanical issues persist. What’s more, alarms occur too often. Operators intervene more than they should. Throughput, quality, and energy efficiency fall short of what the process is capable of delivering.

The gap is rarely caused by a lack of control. It stems from a lack of visibility and prioritization. System Health Monitoring (SHM) addresses this gap by helping engineers and operations teams focus on the control problems that matter most to plant performance.

Control Does Not Equal Optimization

Distributed control systems are designed to maintain stability and to optimize production within an established model of a process. However, they are not designed to continuously optimize performance as systems age and dynamic behavior changes. Once commissioned, many PID loops are left untouched unless they cause an obvious problem:

• Equipment ages and mechanical wear increases
• Operating targets shift to meet production demands
• Feedstock and environmental conditions vary

A loop that was acceptable at startup may quietly become a source of variability years later. Without continuous monitoring, these issues remain hidden until they show up as quality losses, energy waste, or unplanned downtime. Continuous control loop performance monitoring—using historian data to assess tuning, variability, and operating state—helps make this type of degradation visible long before it becomes disruptive. Platforms such as PlantESP are commonly used to support this level of plant-wide visibility.

The Hidden Cost of Underperforming Control Loops

Poorly performing loops do not always fail loudly. More often, they introduce small but persistent inefficiencies:

• Increased process variability that limits throughput
• Excessive valve movement that accelerates mechanical wear
• Oscillations that force operators into manual control
• Alarm floods that reduce situational awareness

Individually, these problems may seem minor. Collectively, they erode plant performance and consume engineering time with reactive troubleshooting. Plants that rely primarily on alarms and operator intervention often miss economically significant control issues.

Why Prioritization Is the Real Challenge

Large facilities may rely on hundreds if not thousands—or tens of thousands—of PID control loops. Attempting to tune or troubleshoot them one by one is not practical. The key question becomes:

Which loops are actually limiting plant performance right now?

System Health Monitoring answers this by continuously screening loops and ranking them based on measurable impact. Scaling this type of prioritization beyond a single unit requires enterprise-level analytics, particularly when organizations attempt to extend control performance insight across multiple sites without overwhelming local teams. Rather than relying on anecdotal complaints or alarm counts, SHM uses data-driven metrics to identify:

• Loops with excessive variability
• Controllers operating far from their intended tuning
• Valves exhibiting signs of stiction or saturation
• Processes that no longer match their assumed dynamics

This prioritization allows teams to direct effort where it delivers the greatest return.

Turning Data into Actionable Insight

Effective SHM goes beyond dashboards. It connects performance metrics with diagnostic insight so engineers understand why a loop is underperforming.

For example:

• Mode metrics isolate controllers that operate outside of their assigned function
• Variability metrics highlight loops that require attention
• Output-based analytics expose mechanical issues such as valve stiction

By combining these indicators, SHM transforms raw process data into a clear action list instead of another monitoring screen. Techniques such as controller output analysis used to identify valve stiction and other final control element issues help surface emerging mechanical problems using everyday controller data.

People, Process, and Technology Must Align

Sustainable optimization does not happen through software alone. Plants that succeed with SHM align three elements:

1. People – Clear ownership between operations, reliability, and controls
2. Process – Defined workflows for reviewing metrics and implementing changes
3. Technology – Tools that scale across units, areas, and sites, such as historian-integrated monitoring platforms that support KPI-based prioritization, diagnostic analytics, and long-term performance tracking

When these elements work together, improvements persist instead of degrading over time. SHM becomes part of normal operations rather than a one-time initiative.

From Reactive Troubleshooting to Proactive Improvement

External perspective: Industry analysts and standards bodies such as ISA consistently emphasize that sustained operational excellence requires moving beyond alarm response and toward continuous performance assessment at the control loop level. System Health Monitoring aligns with this guidance by embedding performance evaluation directly into day-to-day operations.

The most significant shift enabled by System Health Monitoring is cultural. Instead of reacting to alarms and complaints, teams proactively identify and resolve issues before they affect production.

This approach delivers measurable benefits:

• Reduced operator intervention
• Improved product quality and consistency
• Lower maintenance costs through early detection
• Greater confidence in control system performance

Conclusion

Plants do not struggle because they lack control systems. They struggle because they lack a structured way to understand which control problems matter most.

System Health Monitoring provides that structure. By continuously evaluating control performance, prioritizing high-impact issues, and supporting data-driven decision-making, SHM enables plants to operate smarter, faster, and better every day.For readers interested in a deeper, example-driven discussion of how System Health Monitoring is applied in real plants, a related webinar is available: Smarter, Faster, Better: Using System Health Monitoring to Prioritize What Matters Most in Optimizing Plant Performance.