A wall screen is not a decision.
Most monitoring projects end at the andon board. The data is correct, the colours are accurate, and nothing in the schedule changes because of it. Visibility without a consequence is decoration with a licence fee.
MACHINE MONITORING · PLANT FLOOR
Machine monitoring software that ends in a decision, not a screen
Every plant that installed monitoring can tell you what happened. Very few can tell you what to do about it by Thursday.
THE SHORT ANSWER
Machine monitoring collects machine state and turns it into live visibility: running, idle, stopped, why. That is the floor, not the ceiling. The version worth buying learns each machine's own normal, flags only deviations from that normal, and hands the finding to planning so the answer becomes a scheduled action with a human sign-off.
WHAT THE MARKET SELLS AS MONITORING
Generic thresholds fire on personality, not on faults.
Two identical machines are never identical. One runs warmer since the day it was installed. A shared threshold turns that permanent quirk into a daily alarm, and within a month the team mutes the channel.
Monitoring is sold as a hardware project.
The default quote starts with gateways and sensor kits. Meanwhile the PLCs, the SCADA tags and the historian have been recording the same machines for years, unread.
The market sells monitoring as more screens.
Atherya reads the machines you already record, and answers in decisions.
WHAT ATHERYA DOES INSTEAD
It starts on existing data.
OPC-UA and PLC/SCADA tags, SQL historians, MES, ERP, CMMS. Sensors come later, only where physics genuinely requires them — never as the entry ticket.
One normal band per machine.
Each machine gets its own learned normal, per recipe and per shift. A deviation is measured against that machine's history, not against a manual written for the model.
Every signal carries its evidence.
Which signal moved, over which history, against which comparable event. A monitoring alert you can argue with is one your maintenance lead will actually open.
The finding becomes a window.
Atherya proposes when the machine should stop, against the live production plan, and waits for approval. Monitoring that ends in a calendar entry instead of a notification.
READ FROM ONE REAL PLANT — BEFORE INSTALL
6years of raw history6Mreadings · 42 machines · 5 families141machine × recipe signatures98 → 7open questions closed from data
Rubber moulding, northern Italy. Figures from a real onboarding, read from existing data before any installation. Anything beyond them is a scenario, and we declare it as a scenario.
HOW IT WORKS ON A REAL PLANT
- The first read is historical, not live: six years of raw history, roughly 6 million readings across 42 machines in 5 asset families, before a single installation.
- From that read, 141 machine × recipe signatures were learned and 98 open questions about the plant were reduced to 7 that genuinely needed a person.
- The bottleneck was not where the plant assumed: 60.8% of it concentrated on the presses. And the same recipe produced 5.9% more output at night — visible only once each machine was compared with itself.
What makes Atherya different
Most predictive maintenance tools score signals. Atherya builds an operational memory of the plant first, then reasons on top of it — with the evidence in plain sight and the decision left to a person.
Operational memory
Every event, anomaly, intervention and shift becomes shared memory. What was a log yesterday is experience tomorrow, and the model reads new signals against it.
Déjà Vu: it has seen this before
Not just "anomaly detected", but when it already happened, how similar it was, how it evolved and which action worked. The senior maintainer's memory, available to everyone.
Context that kills false alarms
Machine defects, weak points, how the crew actually works and the environment around the line. A deviation that is normal for that machine, that shift or that season stays quiet.
Living FMEA
FMEA, manuals and procedures become an active part of the reasoning: causes, effects, sensors and suggested actions are connected, instead of sitting in a document nobody opens.
Explainable, not magic
Every alert arrives with the signals involved, the comparable history, the failure mode and a confidence level. Data, interpretation and decision stay separate and verifiable.
It acts, with your sign-off
Atherya does not stop at the warning: it proposes the maintenance window against real orders and shifts, and replans when something changes. Nothing is applied until a person approves it.
On the data you already have
It works on PLC, SCADA, MES, ERP, maintenance records and feedback as they are — fragmented and legacy included. Sensors are added only where no existing signal carries the degradation.
One brain, not a maintenance silo
Maintenance, production and planning read the same operational state, so a predicted failure immediately becomes a scheduling question instead of a separate dashboard.
QUESTIONS, ANSWERED
Straight answers.
What is machine monitoring software?
Software that collects machine state — running, idle, stopped, cycle counts, reasons — from PLC, SCADA or historian sources and makes it visible in real time. Modern systems add analysis on top: comparing each machine with its own history instead of only reporting its current state.
Do I need new sensors for machine monitoring?
Usually not to start. Most plants already record enough through PLC/SCADA tags, a historian, the MES and the CMMS. Atherya reads those first; sensors are added later only where the physics genuinely needs them.
Why do monitoring alarms get ignored?
Because they fire on generic thresholds. Each machine has permanent quirks that look like faults to a shared rule, so the channel fills with noise and the team mutes it. Learning a per-machine normal band is what removes that noise.
How is this different from an OEE dashboard?
An OEE dashboard scores the past. Monitoring with a learned normal explains what changed and why, and then feeds the maintenance and production plan so the answer becomes a scheduled action.
Does Atherya act on the machine by itself?
No. It replans and proposes — the maintenance window, the trade-off it made — and waits for human sign-off. Every decision leaves an auditable trail.
YOUR PLANT · YOUR DATA · THE PROOF
Point it at the machines you already record.
Send an export of what your machines already produce. We read it and give you back your plant's story.
Discover Atherya