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Maintenance triggered by the machine. Not by the calendar.

Real machine condition — MTBF and MTTR per machine, downtime reasons from the floor, wear-part counts — turned into maintenance tasks with owners and dates. Complements your CMMS. Does not replace it.

Request a demo your worst machine · 30 minutes How it fits your CMMS ↓

Maintenance technician working inside a CNC machining centre

MTBF / MTTRper machine, live

Tasksassigned, tracked to done

Your CMMSfed by VF, not replaced

The problem

Preventive maintenance runs on a calendar. Machines don't.

The PM schedule treats every machine the same: too early for the ones that sat idle, too late for the ones that ran three shifts. And when a breakdown does happen, the reason is missing, the fix is undocumented and the next one is a surprise again.

Too early on some machines, too late on others

A calendar cannot see hours run, cycles made or how a machine actually behaved this month.

Breakdowns explained after the fact

Downtime is logged as "mechanical". The pattern that preceded it — short stops, slow cycles, a rising reason count — was never captured.

Findings die between shifts

The technician notices, the operator mentions it, nobody writes the task. The next stop is the same stop.

The machine already tells you when it needs attention. Someone has to listen.

What you get

Reliability measured. Reasons captured. Actions assigned.

Visual Factories reads every machine's real behaviour and turns it into maintenance work that gets done — from the same connection that runs OEE.

MTBF

41 h

↑ from 29 h

MTTR

38 min

↓ from 66 min

Breakdowns

this week · 3 machines

Machine 04 · top reason: hydraulic pressure (4 stops) — task assigned

01 · Reliability per machine

MTBF, MTTR and breakdown minutes — live, per machine

Not estimated at month-end: measured from the machine's own signals as it runs. Trends show which machines are getting worse before they fail.

02 · Reasons from the floor, ranked by AI

Every stop tagged. The pattern found.

Operators add the reason in one tap. The AI agent ranks losses by what they cost — including the micro-stops the Pareto misses — and recommends the maintenance action.

03 · Tasks & wear parts

From finding to work order to done

One click turns a finding into a task with an owner and a due date. Bearings, filters, belts and other wear parts raise their own alerts before they fail. Daily PDF to the maintenance manager; the evidence goes to your CMMS.

The maintenance task board — every finding becomes a task with a machine, an owner, a priority, a due date and a status

Visual Factories tasks tracking — maintenance tasks with owner, priority, status and due date

Where it fits

Visual Factories feeds your CMMS. It does not replace it.

A CMMS is the system of record: assets, PM calendar, spare parts, work orders. Visual Factories is the system of condition: what the machine is doing right now, why it stopped, and what should be done about it — with the evidence attached.

Visual Factories — condition

Live machine truth, turned into action

MTBF / MTTR and breakdown minutes per machine, from the signals
Stop reasons from the floor, ranked by the AI agent
Wear-part alerts (bearings, filters, belts) before the failure
Tasks created, assigned and tracked to done
Daily PDF and analytics for the maintenance manager

→

Your CMMS — record

Assets, calendar, parts, work orders

Asset registry and full maintenance history
Preventive-maintenance scheduling by date or usage
Spare parts and MRO inventory
Work-order lifecycle and costing
Compliance records and audits

Condition triggers the work. The CMMS records it. Neither one alone gets the machine fixed before it stops.

How it works

Detect. Diagnose. Assign. Verify.

The same closed loop that improves OEE — pointed at reliability.

01 · Detect

The signal changes first

More short stops, slower cycles, rising breakdown minutes on one machine. The trend is visible days before the failure.

02 · Diagnose

Reasons and the AI ranking

Operators tag the stops; the AI agent finds the main reason and recommends the action.

03 · Assign

A task with an owner

One click creates the maintenance task — assigned, dated, tracked. Or push it to the CMMS as a work order.

04 · Verify

MTBF proves it

After the fix, the machine's own MTBF and MTTR show whether the problem is gone — no opinion required.

AI in action

Measurement becoming maintenance.

The AI agent finds the reason behind a loss, recommends the action and creates the task — assigned to the right person and tracked through to done.

See the OEE Improvement application →

Managers reviewing Visual Factories AI analysis on a tablet

Consumables & wear parts

The wear parts tell you when.

Bearings, filters, belts, seals, lubricants: anything maintenance has to replace on time — with a life in cycles or hours — is counted by the machine and raises its own alert, so the change is a planned stop, not a breakdown.

Counted

Cycles and hours from the machine

Every wear part with a standard life is tracked against the machine's real use, not the calendar.

Alerted

Before end of life

The alert lands on the floor monitor and the phone while a planned stop is still ahead.

Connected

Same device, same login

The IoT device the electrician installs in under an hour feeds condition, wear-part counts and OEE from one connection — the Universal Adapter in the cloud does the rest.

Floor aisle with Visual Factories monitor

What changes

From calendar maintenance to condition maintenance.

Today

PM by calendar — same interval for every machine
Breakdown reasons written after the fact, or not at all
Findings lost between shifts
Wear parts changed on a guess

With Visual Factories

Maintenance triggered by real condition and use
Every stop tagged, patterns ranked by the AI
Tasks with owners, tracked to done, evidence in the CMMS
Wear parts changed at a planned stop

Who uses it

Maintenance manager

Works the worst machine first

MTBF/MTTR per machine ranks the fleet. The daily PDF says what happened and what is open.

Technician

Gets a task, not a rumour

Reason, machine, history and due date on the phone. Closes it when done.

Production manager

Fewer surprise stops

Planned stops replace breakdowns; the OEE availability line moves.

Plant manager

Sees reliability improving

MTBF trend by machine, month over month — proof the program works.

Free download

Condition-based maintenance — readiness checklist

What your machines already report, what a CMMS needs from it, and the ten questions to answer before you connect the first machine — two pages for maintenance and production managers.

PDF · 2 pages · to be drafted