Live OEE by machine
Every machine's OEE updated in real time as the shift runs — so supervisors know which line needs attention now, not tomorrow morning.
The problem
Why OEE tracking fails without automation
Manual OEE is always incomplete, always late, and almost always inconsistent between shifts. The result is a number you can't trust and can't act on.
01
The data is always from yesterday
Shift logs get compiled the next morning. Timestamps are rounded. Shift A excludes changeovers; shift B doesn't. By the time the OEE figure reaches your inbox, the loss it describes is already locked in — and the methodology debate has already started.
02
The invisible losses are the expensive ones
Micro-stops under 2 minutes never appear in a log. A machine running at 75% of its rated speed looks fine to anyone walking past. A quality defect cluster that started at 14:00 shows up in tomorrow's scrap report. These losses are consistent, repeatable — and fixable, if you can see them.
03
You're buying capacity you already have
The average manufacturer runs at 60–65% OEE. World-class is 85%. That gap is not a machine shortage — it's recoverable capacity inside your existing equipment. A €400k machine doesn't help if your current lines are running at 58%.
How it works
Each factor captured directly from the machine — not from a log
Availability, Performance and Quality each have a data source. hopit reads them from the machine signal in real time, so the number reflects what actually happened — not what someone remembered at shift end.
Availability · Performance · Quality
Each factor separated — so you know which lever to pull, not just that OEE is low.
90%
Quality
70%
Perf.
80%
Avail.
Machine timeline with downtime events
A chronological record of every stop — with cause, duration precise to the second, and how each event maps to the OEE figure.
Shift and line analytics
Filter by machine, line, shift or time period. All measured with the same formula — so comparing this quarter to last quarter is finally meaningful.
See it running on your kind of line
Try our free online demo — the same dashboards, live.
TRY OUR FREE DEMOFeatures and what they change
Each capability changes something specific
✓
Real-time OEE dashboards — shop-floor visibility while there's still time to act. A supervisor who sees 58% OEE at 2 PM can still recover the afternoon. That conversation used to happen the next morning.
✓
A · P · Q breakdown — know which lever to pull. Low Availability means downtime. Low Performance means speed loss or micro-stops. Low Quality means a process or material issue. Each calls for a different intervention.
✓
Downtime and reason-code tracking — root-cause identification in structured form. Every stop categorized, timestamped, and ranked by the production time it cost. Over time this becomes the data that drives maintenance prioritization.
✓
Automated data collection — eliminates manual logging errors. Machine timestamps are precise to the second. There's no human in the loop calculating or estimating — the data is exactly what happened.
✓
Shift, line, and plant-level comparisons — benchmarking across your operation. Every data point collected the same way — so when you compare Line A to Line B, or this quarter to last, the comparison is actually valid.
Who it's for
Roles and industries
Roles
✓
Plant Managers & Operations Directors — need a consistent OEE number across all lines and shifts for management reporting, capacity planning, and investment decisions.
✓
Continuous Improvement & Lean Leads — need structured loss data to prioritize Kaizen events, run root-cause analysis, and track whether improvements actually moved the number.
✓
Maintenance Managers — need downtime data by cause and machine to justify maintenance resources and prioritize the backlog.
✓
Production Supervisors — need real-time visibility during the shift to intervene before losses compound.
Industries
hopit is purpose-built for small and medium-sized manufacturers in the DACH region running machines or production lines. Common sectors:
Metalworking and precision machining
Plastics and injection moulding
Electronics and PCB assembly
Food and beverage processing
Packaging and converting
Automotive components and subassembly
Medical device manufacturing
Frequently Asked Questions
The first machine is typically connected within hours. A full plant deployment — multiple lines, all machines — takes most customers under two weeks. We handle onboarding and machine connection together with you.
Yes. hopit Edge supports protocols that cover equipment going back decades — Modbus, Siemens S7, digital I/O relay outputs, and more. If the machine has any readable electrical signal, it can be connected.
hopit Edge runs on your local network and collects machine data on-premises. That data is sent to hopit's EU-hosted infrastructure, where the Manufacturing dashboard runs. An internet connection from the Edge machine is required.
You can start with Availability alone. Machine state signals are often the easiest first connection. Performance and Quality can be added as you bring more data sources online. You don't need everything wired up on day one.
No — it complements it. hopit is focused on real-time machine performance data and OEE. MES handles orders, scheduling, and production planning. They solve different problems and can run alongside each other.
Machine data is collected by hopit Edge and sent to hopit's EU-hosted infrastructure over an encrypted connection. Access is role-based — admins, managers, and operators each see what's relevant to their role. All connections use TLS encryption.
See your real OEE — starting this week.
Try the live demo to see what OEE looks like when it comes from the machine signal. Or talk to us about connecting your first line.