Overall Equipment Effectiveness (OEE) is the number plant managers ask for first and the one that's hardest to get honestly. In food and beverage — filling, packaging, blending, case-packing — the line never stops moving, micro-stops hide everywhere, and the "ideal rate" everyone quotes is usually optimistic. A good OEE dashboard cuts through that. Here's how we build one on Ignition Perspective, and why the platform fits this job well.
What OEE actually measures
OEE is the product of three factors, and the discipline is in keeping them separate:
Availability — the share of scheduled production time the line was actually running, after planned and unplanned downtime. Performance — how fast it ran versus its ideal cycle time when it was running (this is where micro-stops and slow running hide). Quality — the share of product that came off good the first time, no rework or scrap. Multiply the three and you get OEE. A line at 90% availability, 95% performance and 98% quality is running at about 84% OEE — and the dashboard's job is to show which of those three is bleeding.
Why Ignition is a good fit for OEE
Two reasons stand out. First, the licensing model: Ignition is licensed by server, not by tag or by client, so instrumenting every machine on a line with run-state, counts and downtime tags doesn't inflate the bill the way per-point platforms do. Second, the data path is short — the same gateway that polls the PLCs over OPC UA also logs to a SQL database and renders the Perspective screens, so there's no middleware to keep in sync. For deeper plant-wide OEE, downtime tracking and scheduling, the Sepasoft MES modules layer cleanly on top — the same approach we use for MES on dairy lines.
Get the data layer right first
Every bad OEE dashboard we've been called in to fix had the same root cause: the data underneath it was wrong. Before any charts, nail down three things at the PLC and tag level:
Run state and scheduled time — you need an unambiguous "this line is supposed to be running now" signal, and a clean running/stopped/faulted state. Define those as UDT members so every line reports them identically. Counts — good count and reject count straight off the machine, totalized carefully so a PLC power cycle doesn't zero your shift. Ideal cycle time — the real, demonstrated best rate for each product, not the nameplate number. Performance loss is meaningless if the denominator is fiction.
Capture downtime reasons at the source
Availability without reasons is just a sad number. The payoff comes from a downtime reason model: when the line stops longer than a threshold, the operator picks a reason from a short, hierarchical list (changeover, jam, upstream starve, downstream block, mechanical, sanitation). A Perspective screen at the line with big touch targets makes this realistic on a wet plant floor. Auto-classify what you can from PLC state, and only ask the operator for what the controller can't know.
Designing the dashboard
We build OEE views in three layers so each audience sees the right altitude:
Plant / line overview — a tile per line with live OEE, current state, and the limiting factor highlighted, so a supervisor sees at a glance where to walk. Line detail — the OEE waterfall (availability → performance → quality), a downtime Pareto for the shift, and a speed-vs-ideal trend. The Pareto is the single most actionable chart on the screen; it tells maintenance where the hours are going. Drill-down — a sortable, filterable event log of every stop with its reason, duration and timestamp. This is exactly the kind of dense, interactive table where the stock Perspective table runs out of road, which is why we built Perspective DataGrid Pro.
Reporting and historical analysis
Live screens drive the shift; reports drive improvement. Roll OEE up by shift, day, product and line into the historian and SQL, and let teams compare last week to this week, or product A to product B on the same line. A scheduled daily OEE report — emailed each morning — keeps the metric in front of leadership without anyone opening a screen.
Common pitfalls
Optimistic ideal rates inflate availability and hide performance loss. Ignoring micro-stops (sub-minute stops that never get a reason) understates your biggest improvement lever. Counting at the wrong point on the line double-counts or misses reject loops. And no operator buy-in on reason codes means garbage data within a week — keep the list short and the screen fast.
Where we come in
We design and build OEE and downtime systems on Ignition for plants across California's Central Valley — food and beverage, dairy, poultry and packaging — and remotely for teams anywhere in the US. If you want OEE you can actually trust, get in touch or see the full range of Ignition development services we offer. We're based in Merced, in the heart of the Valley's food and ag corridor.