Analyzer Reliability vs Accuracy – What Really Matters?

In analyzer datasheets, accuracy gets the spotlight. In real plants, reliability decides everything.

Engineers often debate analyzer accuracy in decimals and percentages. Technicians, however, face a different reality: an analyzer that is perfectly accurate but frequently unavailable is practically useless.

An accurate analyzer that is down gives zero value. A reliable analyzer gives usable information every day.

What Is Accuracy?

Accuracy refers to how close a measurement is to the true value. It is usually defined under ideal laboratory conditions.

These conditions rarely exist in operating plants.

What Is Reliability?

Reliability is the analyzer’s ability to:

Reliability means operators trust the number they see.

Why Reliability Matters More in Real Plants

1. Control Needs Trends, Not Perfection

Process control reacts to trends. A stable, repeatable signal is more valuable than a theoretically perfect one.

2. Alarms Depend on Availability

An analyzer in maintenance mode cannot protect equipment or people. Reliability ensures alarms are active when needed most.

3. Environmental Compliance Is Continuous

Regulators care about data availability as much as accuracy. Missing data periods often cause more trouble than small bias errors.

Common Causes of Poor Reliability

Most analyzer failures are caused by sample systems — not analyzers.

The Technician’s Role

A slightly less accurate analyzer that is always online is more valuable than a highly accurate analyzer that frequently fails.

Conclusion

Accuracy impresses on paper. Reliability delivers in the field.

The best analyzer systems are those that technicians can keep running, operators can trust, and plants can depend on.