May 27, 2026

PID Loop Tuning In Industrial Automation: Joe Virag On Why Process Control Still Matters In Modern Manufacturing

PID Loop Tuning In Industrial Automation: Joe Virag On Why Process Control Still Matters In Modern Manufacturing

PID loop tuning may not be the flashiest topic in industrial automation, but according to Joe Virag, it remains one of the most important and most misunderstood.

In our latest live of Automation Ladies, the conversation focused on the realities of process control, why PID tuning still feels like the “wild west” in many facilities, and how proper tuning can dramatically impact manufacturing performance, stability, and efficiency.

The discussion explored not only the technical side of PID loops, but also the practical challenges engineers, technicians, and manufacturers face every day when trying to optimize real-world industrial systems.

From troubleshooting unstable loops to improving operator confidence and understanding why tuning is often neglected, this live delivered a very honest look at what process control actually looks like on the plant floor.

What Is PID Loop Tuning?

PID stands for:

  • Proportional

  • Integral

  • Derivative

These control loops are used throughout industrial automation to regulate variables such as:

  • Temperature

  • Pressure

  • Flow

  • Speed

  • Level

  • Motion

PID loops exist in nearly every manufacturing environment, from food and beverage to oil and gas, water treatment, pharmaceuticals, packaging, and discrete manufacturing.

And while PID control has existed for decades, many facilities still struggle with tuning loops properly.

As discussed during the live, it’s common for plants to have loops that technically “work” but are far from optimized.

That matters more than many people realize.

Poorly tuned PID loops can create:

  • Instability

  • Oscillation

  • Excessive wear on equipment

  • Increased energy consumption

  • Product inconsistency

  • Operator frustration

  • Downtime

  • Reduced production efficiency

Even small tuning improvements can have major operational impact across an entire facility.

Why PID Tuning Still Feels Like The Wild West

One of the most interesting parts of the conversation was the acknowledgment that PID tuning is still often handled very differently from plant to plant.

In many facilities, tuning knowledge lives inside the heads of experienced engineers or technicians.

Sometimes tuning adjustments are based on:

  • Trial and error

  • Historical habits

  • “What worked last time”

  • Tribal knowledge

  • Emergency troubleshooting

And while there are established tuning methodologies, real-world manufacturing environments rarely behave perfectly.

Every process has:

  • Different dynamics

  • Different delays

  • Different mechanical constraints

  • Different operational priorities

That’s why PID tuning remains both technical and highly practical.

It’s not just about formulas.

It’s about understanding the process itself.

The Human Side Of Process Control

A major theme throughout the episode was that process control is not only about technology, it’s also about people.

Operators and technicians often work around unstable loops every single day.

Sometimes systems become so normalized in their unstable state that teams stop questioning whether performance could actually be improved.

That’s where experienced process control professionals become incredibly valuable.

Proper tuning can help:

  • Improve operator confidence

  • Reduce manual intervention

  • Stabilize production

  • Improve product quality

  • Create more predictable operations

And in many cases, the improvements are noticeable almost immediately.

Why Modern Manufacturing Still Depends On Strong Fundamentals

One of the strongest takeaways from this episode is that advanced manufacturing technology still depends heavily on foundational engineering principles.

AI, digital transformation, Industry 4.0, and advanced analytics are becoming larger parts of industrial automation every year.

But none of those technologies eliminate the need for:

  • Stable control systems

  • Reliable instrumentation

  • Strong engineering practices

  • Process understanding

  • Good operational fundamentals

If the underlying control strategy is unstable, adding additional software layers or analytics often does not solve the root problem.

That’s why conversations like this remain so important.

Modern manufacturing is evolving quickly, but strong process control continues to sit at the center of reliable operations.

Why Process Control Knowledge Matters For The Next Generation

Another important element of the conversation was education.

As experienced automation professionals retire, there is growing concern across the manufacturing industry about preserving practical process control knowledge.

PID tuning is one of those skill sets that often gets learned through:

  • Field experience

  • Troubleshooting

  • Mentorship

  • Real-world system exposure

And while simulation tools and AI-assisted engineering platforms continue improving, there is still enormous value in understanding how systems behave physically in the real world.

For younger engineers and technicians entering industrial automation, learning process control fundamentals can create major long-term career advantages.

Because no matter how advanced manufacturing technology becomes, facilities will always need people who understand how to make systems run reliably.

Final Thoughts

This Automation Ladies live with Joe Virag was a great reminder that some of the most impactful topics in industrial automation are not always the newest ones.

PID loop tuning has been part of manufacturing for decades.

And yet, it continues to shape:

  • Production quality

  • Operational efficiency

  • Equipment reliability

  • Energy usage

  • Plant stability

  • Workforce productivity

As manufacturing continues modernizing, the companies that succeed will likely be the ones balancing new technology adoption with strong engineering fundamentals.

Because before AI can optimize a process, the process itself still needs to run well.