How do you calculate PLC data availability?

Multiply tags per scan cycle by planned cycles for gross capacity, then multiply by scanner uptime and clean-poll rate. With 500 tags, 60 cycles, 99% uptime, and 99% clean-poll, gross is 30,000 and good polls are 29,403 per period.

What is a good clean-poll rate for OPC scanning?

A healthy, well-tuned OPC UA or DA connection sustains 99%+ clean polls without retry. Dropping below 97-98% usually points to network congestion, an undersized scan rate, or a PLC CPU that cannot service the request load.

Why does 99% uptime and 99% clean-poll not give 99% good polls?

The two losses compound. Scanner downtime removes 300 tags and retries remove another 297, so 597 of 30,000 are lost and only 29,403 land — roughly 98%, not 99%, because the factors multiply rather than add.

Scanner uptime vs clean-poll rate — what is the difference?

Scanner uptime is the fraction of time the OPC scanner or gateway is online and polling at all. Clean-poll rate is the fraction of attempted polls that return valid data on the first try, without a retry or timeout, while the scanner is up.

How do I improve good PLC poll yield?

Harden the gateway and its power/network path to lift uptime, then reduce retries by matching scan rate to PLC capability, segmenting tags across connections, and fixing slow or oversized address ranges. Each percentage point recovered here is worth roughly 300 tags.

Does this account for tag staleness?

Indirectly. A dropped or retried poll often means the historian keeps the previous value, which shows up as staleness. This calculator counts the delivered good polls; pair it with a deadband or update-rate check to quantify staleness itself.

IIoT, SCADA & Edge Connectivity calculator

PLC Data Availability Calculator

PLC Data Availability measures how many of your planned PLC tag reads actually land cleanly over a period once scanner downtime and poll retries are removed. SCADA, IIoT, and controls engineers use it to size historian throughput, validate that an OPC UA gateway can keep up with the tag count, and put a number on data completeness for downstream analytics and OEE. It matters because dashboards, alarms, and machine-learning models silently degrade when tags are stale or dropped — and a 99% clean-poll rate that sounds fine still loses hundreds of reads per cycle at scale. Knowing your good-poll yield lets you set realistic data SLAs instead of assuming every scan reaches the database.

What this calculator does

Estimate how many PLC tags can be polled cleanly per period from tags polled per scan cycle, planned scan cycles in the period, scanner uptime, and the share of polls that return fresh data without retry.
Use it when a controls engineer is sizing the PLC scanner load on Kepware, FactoryTalk Linx, or a vendor OPC UA server before adding more tags or another machine to the line.
It computes good PLC tag polls per period by multiplying tags per scan cycle by planned cycles, then derating by scanner uptime and the clean-poll rate.

Formula used

Gross PLC poll capacity = tags per scan cycle × planned cycles
Good PLC poll capacity = gross capacity × scanner uptime × clean-poll rate

Inputs explained

Tags polled per scan cycle: Use the count of tags configured in the active OPC scan group (typical 100 to 5000 tags per group depending on PLC and bandwidth).
Planned scan cycles in the period: Use the planned cycles in the period (60 per minute at 1 second scan, 600 per minute at 100 ms scan).
OPC scanner uptime: Use the share of the period the OPC scanner was actually running (typical 99+ percent on a healthy server; lower if the PLC went into program mode or the network dropped).
Clean-poll rate without retry: Use the share of polls that returned fresh data on the first attempt (typical 98 to 99.9 percent for a stable PLC; lower if the PLC is overloaded or on a noisy network).

How to use the result

Use it when scoping an OPC/edge gateway, a historian ingest rate, or a data-quality SLA and you need expected delivered tag volume, not theoretical.
It assumes uptime and clean-poll losses are independent and uniform; bursty network faults or a single offline PLC can concentrate losses in ways this average hides.

Current U.S. benchmarks

Global copper trades at $13,484 per tonne (IMF via FRED, May 2026), up 41.5% in a year, and U.S. industrial electricity averages 8.66 cents per kWh. Both feed electrified-hardware unit economics.

Common questions

How do you calculate PLC data availability? Multiply tags per scan cycle by planned cycles for gross capacity, then multiply by scanner uptime and clean-poll rate. With 500 tags, 60 cycles, 99% uptime, and 99% clean-poll, gross is 30,000 and good polls are 29,403 per period.
What is a good clean-poll rate for OPC scanning? A healthy, well-tuned OPC UA or DA connection sustains 99%+ clean polls without retry. Dropping below 97-98% usually points to network congestion, an undersized scan rate, or a PLC CPU that cannot service the request load.
Why does 99% uptime and 99% clean-poll not give 99% good polls? The two losses compound. Scanner downtime removes 300 tags and retries remove another 297, so 597 of 30,000 are lost and only 29,403 land — roughly 98%, not 99%, because the factors multiply rather than add.
Scanner uptime vs clean-poll rate — what is the difference? Scanner uptime is the fraction of time the OPC scanner or gateway is online and polling at all. Clean-poll rate is the fraction of attempted polls that return valid data on the first try, without a retry or timeout, while the scanner is up.
How do I improve good PLC poll yield? Harden the gateway and its power/network path to lift uptime, then reduce retries by matching scan rate to PLC capability, segmenting tags across connections, and fixing slow or oversized address ranges. Each percentage point recovered here is worth roughly 300 tags.

Last reviewed 2026-05-12.