Process automation & KPIs
Higher OEE, better on-time delivery and shorter lead times. Less scrap, less downtime and faster response times. We measure, analyse and automate — with real data from your production.
Typical KPI drivers we address
- Unplanned downtime — detected too late, fixed too slowly
- Changeover times that better planning could cut significantly
- Scrap caused by process parameter drift that goes unnoticed
- Capacity bottlenecks caused by a lack of transparency on machine utilisation
- Shift reports that aren't available until the next morning
What we deliver
OEE baseline & root-cause analysis
Measure first, then optimise. We determine your current OEE and analyse exactly where the losses come from — availability, performance or quality.
Real-time KPI dashboards
Production managers, shift supervisors and plant management see the same figures — live. Automatic shift reports, with no manual effort.
Alerting & escalation
If OEE falls below target or a process deviates, an alert goes out immediately — via Teams, email or SMS. No more silent problems.
Automated control loops
Where it makes sense, we automate responses: replenishment, rescheduling, parameter adjustment — without manual intervention.
Reference projects
Frequently asked questions
What is a realistic OEE improvement target?
In our projects we typically see an OEE increase of 8–15 percentage points within the first 3 months after go-live — provided the data foundation is right.
Do we need to buy new machines?
No. OEE improvements almost always come from making better use of existing capacity — not from new hardware.
What is the difference between OEE and availability?
OEE combines availability, performance and quality. A machine with 95% availability can still have an OEE of 65% if it runs slowly or produces scrap.
How quickly will I see the first results?
The first dashboards and transparency are in place within 4–6 weeks. Measurable KPI improvements are visible after 2–3 months.