Where yield leaks, and why.
Quality & Yield turns your MES, QMS and checkweigher data into a live view of first-pass yield, scrap, giveaway and defects. See which line, product and process moment drives the loss, built on the systems you already run.
Built on your MES, QMS and checkweigher data · structured on Azure · delivered in Power BI.
See it in action.
An interactive Quality & Yield cockpit, running on sample data. The same layout runs on your lines and products, live.
This is one example view, on synthetic data. Scrap and giveaway stay in percent and units, no euro recovery is claimed until the calculation is hard. On the same governed foundation we shape the screens to your lines, products and 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.
The loss, traced to its cause.
At a glance: what's inside the Quality & Yield dashboard, and what it means for the quality engineer.
Quality KPIs at a glance
First-pass yield, scrap, giveaway, defect rate and batches on hold, in one header that updates through the shift.
First-pass yield per line
Good-first-time split out per line, product and shift, so the line dragging yield down is obvious, not averaged away.
Scrap by cause
Scrap grouped by tagged source per line and shift, so you can tell the recoverable buckets from the structural ones.
Giveaway from the checkweigher
Average overfill above target per line, with the spread that forces the mean up. Shown in grams and percent, no euro figure until it's agreed.
Defect Pareto
Defects ranked by share and traced to where they concentrate, so a few causes, not every defect, get the attention first.
Activate: proposed correction
For a deviating line the system proposes a fix, a setpoint, warm-up or seal-temp change, with a reason code. QA always validates hold and release, and the effect is logged.
How Quality & Yield works.
One reusable path from quality 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 quality data that stays stuck between the checkweigher, the QMS and a stack of paper checks. 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 keep scrap and giveaway in units and percent until a euro figure can be made hard.
“A quality number is only worth acting on if the plant believes it. We start with the data, not the dashboard.”
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, products and 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?
MES production and reject data, QMS quality records, and checkweigher data (per-pack weights and bins). We work vendor-neutral and add the analytics layer on top of what is already there, we do not replace your MES or QMS.
How is first-pass yield calculated?
The share of units that come out good the first time, with no rework or scrap, per line, product and shift. You set the spec and the inspection points, so the number matches how your plant already defines a good unit.
Do you show what scrap and giveaway are worth in euros?
Not by default. We keep scrap and giveaway in percent and units, and separate the recoverable buckets from the structural ones. A euro figure follows only once the recovery calculation is agreed with the plant, so the number holds up rather than inflating the case.
How long until we see a working dashboard?
After a Quick Scan and a short cause- and tag-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 correction, is that AI?
No black box. The Activate layer proposes a fix from transparent, rule-based logic on real signals (for example a fill setpoint or a warm-up rule) with a reason code. QA always validates hold and release before anything happens, and the decision and its effect are logged.