Every line on the floor, on one screen.
Production Performance turns machine, MES and PLC data into a live OEE dashboard for your planners and operators. Output, downtime causes and deviations across every line and every shift, built on the systems you already run.
Built on your PLC, MES and historians · structured on Azure · delivered in Power BI.
See it in action.
An interactive Production Performance dashboard, running on sample data. The same layout runs on your lines, live.
This is one example view, on synthetic data. On the same governed foundation we shape the screens to your lines, your KPIs and your roles, so a different layout is a configuration, not a rebuild.
You're looking at one view of it.
Everything here runs on the same governed data foundation. Build the views you need now, and the ones you need later, on top of it.
Production Performance
OEE, downtime and deviations per line
Delivery Performance
OTIF, schedule adherence, line load
Quality & Yield
First-pass yield, scrap, defect causes
Your own view
Shaped to your KPIs, no rebuild
Built once, shaped to you. Because every view runs on one governed foundation, a different view, or a new one next year, is a configuration, not a rebuild.
Everything the floor needs, on one screen.
At a glance: what's inside the Production Performance dashboard, and what it means for your shift.
Production KPIs at a glance
OEE, output versus target, downtime, lines running and first-pass quality, in one header that updates through the shift.
Prioritised active downtime
Every stop and deviation, ranked by impact, with the affected line, the cause code and the recommended next action attached.
Downtime reason analysis
A Pareto of stop causes per line and per shift, so the recurring losses that eat your OEE are obvious, not buried.
OEE breakdown per line
Availability, performance and quality split out per line and shift, against design rate, so you see exactly where the loss sits.
Shift & line comparison
The same KPIs side by side across shifts, lines and sites, so a gap between teams or plants becomes a fact, not a feeling.
Activate: proposed root cause
For a deviating line the system proposes a likely cause with reasoning and a reason code. Your planner or operator validates, and the choice is logged.
How Production Performance works.
One reusable path from machine signal to dashboard. Built once, then applied across every line and every site.
Built once. Every new line and site inherits the same model, no rebuild.
The people behind the dashboards.
StriData was built by industrial data practitioners who got tired of two things: dashboards no one acts on, and production data that stays stuck between MES, ERP and the planner's own spreadsheet. We work where operational reality meets business outcomes, one foot in IT and one on the floor.
We build the foundation and the analytics on top of what you already run. We are honest about scope, and we say no to work we can't do well.
“A number only steers the plant if everyone trusts it. That is what we build.”
Questions teams ask us.
What if this view isn't exactly what we need?
That's the point. What you see is one example. Because it runs on a governed data foundation, a different view is a configuration, not a rebuild: we reshape the KPIs, layout and screens to your lines and your roles without touching the plumbing underneath. The modules show what's possible; your version is shaped in the Quick Scan.
What data source does it run on?
Machine and PLC signals, MES production and downtime records, historians (PI System, AVEVA), and ERP context where needed. We work vendor-neutral and add the analytics layer on top of what is already there, we do not replace your MES or controls.
Is the dashboard real-time?
Near real-time. Data is loaded incrementally (typically every 15 minutes for the pilot, tunable per setup). Live line state, active downtime and the shift's output update through the day.
Do you build the dashboards, or can our team?
Both. We deliver the Production Performance dashboards on the structured foundation, and because that foundation is open (a governed SQL layer), your own BI team can build directly on it too. No lock-in.
How long until we see a working dashboard?
After a Quick Scan and a short tag- and downtime-mapping workshop, a first working dashboard on a pilot line typically lands in a few weeks. New lines and sites then inherit the same model.
The proposed root cause, is that AI?
No black box. The Activate layer proposes a likely cause from transparent, rule-based logic on real signals (for example dose drift or cycle-time creep) with a reason code. Your planner or operator always validates before acting, and the decision is logged.