For plant and logistics operators
See your equipment, stock and shipments as they move
Real-time data for manufacturing and logistics means streaming events from machines, warehouses and carriers into one governed platform, checking them on arrival and showing them on agreed definitions. Your teams can then spot a failing machine or a late shipment while there is still time to act.
01 Sound familiar
Sound familiar?
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Machine data stays on the line. Maintenance hears about a fault when the machine stops, not from the readings that started drifting days before.
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Stock, orders and shipments sit in different systems, so finding out where an order is takes three exports and a call to the warehouse.
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Each site counts downtime, scrap and on-time delivery its own way, so the monthly figures start an argument instead of a decision.
Explore the layers
Follow a reading from the sensor to the dashboard
Select a layer of a real-time pipeline to see what it does, and what we would settle with your operations and IT teams at that point.
Events from equipment and logistics systems stream through ingestion and processing into governed storage, then out to live dashboards and alerts.
- Sensors and systems
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We would start with what already produces data: machine controllers, historians, the warehouse system and carrier feeds. Access to equipment is agreed with your operations and IT teams before anything is connected.
- Equipment telemetry
- Warehouse and carrier events
- Edge and ingestion
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Gateways near the equipment hold readings while the network is down, then forward them to an event stream, so a short network outage at a site does not leave a gap in the data.
- Gateways and buffering
- Event streaming
- Stream processing
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Each event is checked for units, ranges and timestamps, then joined to the asset, order or route it belongs to. Short time windows turn raw readings into measures people can read.
- Validation and enrichment
- Windowed aggregates
- Storage
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Recent readings stay quick to query, and history moves to governed storage with lineage, so a maintenance or quality figure traces back to the machine and the moment it came from.
- Recent readings
- Governed history
- Dashboards and alerts
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Live views per site, on definitions every site shares. Alert thresholds are set with the people who respond to them, and any predictive maintenance model is tested on your own history first.
- Live operations views
- Maintenance alerts
02 A typical situation
What this usually looks like
An operations director with several sites might come to us with machine data stuck in local historians, stock and shipments spread across separate systems, and a monthly report assembled by hand from each site's own spreadsheet.
We would agree a small set of shared definitions first, then stream events from one line and one warehouse into a governed platform with checks and alerts. Other sites would follow once the people who use that first view trust it.
03 Start
Start with one line, one warehouse or one route
Book a first conversation about which decision waits longest for data. We work within your security review, and we will say if a daily report would do.
What happens next
- You pick a time, or send us a message.
- A person at Nexstella reads what you shared before we talk.
- You leave with a clear next step, even when that step is to wait.
Or write to [email protected]. Send a brief instead
Meet
Booking as .
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Send us two or three times that suit you. A person replies within one business day. The invite goes to the address above.
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What happens next
- You pick a time, or send us a message.
- A person at Nexstella reads what you shared before we talk.
- You leave with a clear next step, even when that step is to wait.
Contact
Send us a message
Pick the topic that fits and tell us what you are working on. A person replies within one business day.
Want the full picture? Read Manufacturing and logistics.
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