Protect your spindle hours
CNCs and VMCs earn by the hour. AssetAI tracks failures to the assembly level, services by run-hours, and tells you which machine deserves replacement — with the cost history to prove it.
How Machine Shops & Engineering plants like yours use AssetAI
Machine shops run on spindle-hours, not calendar dates, which is exactly why generic maintenance checklists fail on the shop floor. AssetAI is built around how a CNC, VMC, or grinding machine actually breaks down — down to the assembly and component, not just "the machine" — so every rupee of repair cost and every recurring failure gets tracked back to its source.
How a Breakdown Gets Logged and Closed
An operator standing next to a machine that's just thrown a spindle alarm doesn't need a login screen — they scan the QR code on the machine, enter their name and company PIN, and the breakdown is logged. That single action kicks off a structured workflow instead of a WhatsApp message to the supervisor:
- A work order is opened against the exact asset, and if it's a corrective or breakdown job, it cannot be closed without selecting a failure cause and failure remedy from your master lists.
- Parts consumed, outside services (a spindle rebuild, for instance), and labour hours all sit on the same work order, so the true cost of that repair is visible against the machine — not scattered across purchase and accounts records.
- Over months, this discipline builds a genuine failure Pareto — recurring bearing failures on a specific VMC, say — instead of a shop-floor folklore of "that machine always has issues."
This structure matters more in machine shops than almost anywhere else, because a five-level equipment hierarchy (Equipment → Assembly → Sub-Assembly → Component → Part) is what lets you tell a spindle-assembly problem apart from a ballscrew sub-assembly problem, rather than lumping every stoppage under "CNC-04 down."
Servicing by Run-Hours, Not the Calendar
Machine shops rarely run every asset the same number of hours a month, which makes calendar-based PM either wasteful or risky. AssetAI's meter-based PM logs run-hours or cycles through the internal screen, a QR-page photo (via OCR), WhatsApp, or API, and fires the next service the moment a logged reading crosses the target — the mechanism behind "servicing by run-hours" instead of by date. It's worth being upfront about the boundary here: this is a logged reading, not a live OPC-UA or MTConnect feed from your CNC controller, so someone still has to capture the number, whether manually or through an integration on your side.
The same time-based scheduling engine also handles gauge and fixture calibration due-dates as one of six schedule types, so recalibration reminders sit alongside your PM calendar rather than in a separate spreadsheet — a small but important detail for shops working toward ISO quality requirements, covered further on our standards page.
Deciding What to Repair, and What to Replace
Every shop has that one VMC that's eaten more in repairs than it's worth — the RRR (Repair/Review/Replace) score puts a number and a readable line of reasoning behind that instinct, using cumulative work-order cost against purchase cost, failure-count trend, downtime cost, machine age, and warranty status. Paired with a downtime-cost Pareto ranking your top assets by rupees lost, it turns a capex conversation from "this machine feels old" into a cost-backed case — useful when your OEE numbers (see our OEE primer) are dragging down shop output per TPM principles. AMC and warranty tracking, plus a structured external-repair workflow for spindle vendors and OEMs, round out the picture for shops that outsource specialist repairs. See the full breakdown on our features page, or book a demo on your own shop floor.
How manufacturing plants like yours use AssetAI
Manufacturing shops in India run a mix of legacy lathes, CNCs still on AMC, and grinding machines bought secondhand — each with a different maintenance rhythm and paperwork trail. AssetAI is built to hold all of that in one system without forcing every asset into the same rigid checklist, which is where most generic CMMS deployments quietly fail on the shop floor.
Calibration, AMC, and Outside Repairs in One Place
A machine shop's compliance load isn't just breakdowns — it's gauge calibration due dates, spindle vendor contracts, and OEM service visits that all need tracking without a separate spreadsheet each:
- Calibration is set up as a recurring schedule (every N days, weeks, or months), so a bore gauge or fixture coming due for recalibration triggers an alert the same way a PM would — useful groundwork if you're working toward ISO-aligned quality processes, more on that on our standards page.
- AMC and warranty details sit against the asset record, so you know whether a spindle repair is billable or covered before the vendor even quotes it.
- When a repair has to go outside — a spindle rebuild at the OEM's facility, for instance — a structured workflow (Requested → Visited → Quoted → ... → Closed) keeps the job visible instead of living in someone's inbox until the machine reappears on the floor.
Where the ₹ Visibility Actually Comes From
Machine shop owners usually know which VMC "gives trouble" by gut feel. AssetAI turns that feeling into a number:
- A downtime cost Pareto ranks your top assets by rupees lost to stoppages, so the conversation about capex shifts from "this machine feels old" to "this machine cost us the most last quarter."
- RRR scoring pulls cumulative work-order cost against purchase cost, failure trend, downtime cost, age, and warranty state into a Repair/Review/Replace verdict, shown as plain reasoning lines rather than a black-box score.
- Where production logs are entered against an asset, OEE is calculated too — see OEE explained for the mechanics — though machines without logged output simply won't have an OEE figure, by design rather than omission.
What AssetAI Deliberately Doesn't Do
Shops evaluating a CMMS against their CNC controllers should know the boundary up front: AssetAI doesn't pull a live OPC-UA or MTConnect feed off the machine, and it doesn't run continuous vibration or temperature monitoring. Run-hours and readings are logged — through the shop floor screen, QR-page photo OCR, WhatsApp, or API — and PM schedules fire off those logged values, not a sensor stream. Similarly, calibration tracking covers recurrence and due dates only, without measurement-uncertainty data or certificate management, and there's no dedicated tool-crib module — a cutting tool needing its own run-hour history has to be modelled as an asset in its own right. If your shop needs that level of sensor integration today, it's worth checking our features list and use cases before you commit; if not, book a demo and see how far logged data alone takes your maintenance decisions.
CMMS for Machine Shops & Engineering FAQs
How do I track spindle and bearing failures across multiple CNC machines to find the root cause?
AssetAI builds a failure history by requiring operators to log the exact failure cause and remedy each time a work order closes—no guesswork. Over time, this creates a trustworthy Pareto chart showing which failure modes (bearing wear, spindle imbalance, tool runout) recur most often and on which machines. The system uses a five-level equipment breakdown structure so failures pinpoint the spindle assembly or ballscrew sub-assembly, not just "the CNC broke." You can then spot patterns—for example, recurring bearing failures on one machine model—and act on real data rather than memory.
Can I schedule maintenance based on machine run-hours instead of just calendar dates?
Yes. AssetAI logs run-hours or cycle counts via the internal screen, QR-page photo OCR, WhatsApp, or API integration, then fires a preventive maintenance work order automatically when the logged reading hits the next target. This means you service by actual machine usage, not elapsed time, so a lightly-used lathe doesn't get serviced as often as a heavily-run one. The system tracks the meter reading continuously, so the schedule is always tied to real production.
What's the real cost of repairing a machine when I have to pay for parts, outside services, and labour separately?
AssetAI combines parts, outside services (such as spindle rebuilds), and labour into one work order tied to that machine, so the total repair cost is visible at a glance. This lets you see the true ₹ cost of each breakdown and track cumulative spending per asset. Over time, you can compare total repair cost against the machine's purchase price to make Repair/Review/Replace decisions on solid numbers rather than guesswork.
How do I know when to repair, replace, or review a machine that keeps breaking down?
The RRR (Repair/Review/Replace) scoring system gives you a verdict per machine by weighing cumulative work-order cost versus purchase cost, failure-count trend, downtime cost, age, and warranty state. The system shows its reasoning in readable lines so you understand why it recommends repair over replacement (or vice versa). This removes emotion from asset lifecycle decisions and aligns them with use-cases like extending asset life or managing obsolescence across your fleet.
How do I make sure my calibration due dates for gauges and fixtures don't slip?
AssetAI has calibration as one of six schedule types, configured as time-based recurring alerts (every N days, weeks, or months). You set the due date once, and the system reminds you when recalibration is due. The work order ties the calibration activity to the specific gauge or fixture, so your traceability record is complete and audit-ready. This is especially important if your shop works to standards like ISO or customer specifications requiring documented gauge history.
Why should operators report breakdowns immediately instead of waiting for the maintenance team to find out?
QR-scan reporting from the shop floor lets operators log a stoppage in seconds—name and company PIN only, no login or app—as soon as spindle or bearing failure happens. This captures the failure in real time while the operator remembers what happened, rather than hours later when details fade. The faster the failure is logged, the faster the maintenance team acts and the sooner production resumes. It also ensures the failure cause is recorded by the person who saw it, not guessed by someone else later.
How do I prevent unplanned downtime when my machine shop relies on tight delivery schedules?
AssetAI lets you schedule preventive maintenance during planned gaps—not rush jobs. Track machine utilization alongside maintenance history to identify safe windows. When breakdowns do happen, log labour costs, parts used, and external vendor charges in one place so you know the true cost of reactive maintenance versus planned upkeep. See work order management for details.