The uptime your OEM audits expect
Presses, welding cells, plating lines and compressors — with customer audits that ask for PM compliance and failure analysis. AssetAI produces both without a single register.
How Auto component manufacturing plants like yours use AssetAI
Auto component manufacturing runs on hundreds of small, high-wear tools — dies, weld guns, fixtures — sitting underneath a handful of expensive machines, and a maintenance record that only tracks the press or the weld cell misses where the actual failure cost lives. AssetAI's asset hierarchy is built to carry both.
Tracking Dies, Fixtures and Weld Guns Without a Separate Tool Module
A press or weld cell is entered once as the parent asset, with commercial data, warranty and AMC terms attached. Dies, jigs, weld guns and fixtures then sit underneath it as child assets in the five-level EBS (Equipment → Assembly → Sub-Assembly → Component → Part), so a die isn't a line item buried in a spreadsheet — it's a node in the same tree as the press that holds it.
- Repair cost against a specific die or weld gun is visible because parts, outside services and labour all post to the same work order as the parent asset.
- Shot counts, cycle counts and run-hours are tracked as meter readings against the child asset, which is how AssetAI approximates die-wear and tool-change timing — via generic meter/condition fields, not a purpose-built die-tracking module.
- AMC and warranty status on compressors and plating pumps is worked out automatically with a fixed precedence — warranty first, then AMC, then expired, then none — so nobody's chasing a vendor contract PDF before raising a work order.
If your plant needs cavity-count-level tool life curves or automated die-change alerts tied to press-stroke counters, treat this as a meter-reading workaround rather than a dedicated tool-management system — worth confirming during a demo against your actual die inventory.
What AssetAI Deliberately Leaves Out
A CMMS covering presses, weld cells and plating tanks touches quality and safety territory without being a quality or safety system, and it's worth being clear on the boundary before you buy:
- There's no IATF 16949 / TS 16949 certification logic built in — PM compliance and failure Pareto come off the standard dashboard and Analytics screens, which auditors generally accept as evidence, but AssetAI itself makes no audit-certification claim.
- Calibration exists only as a maintenance-schedule type. There's no SPC, gauge-quality workflow or CAPA module — that data still needs to live in your quality system.
- There's no permit-to-work entity — no permit number, issue/close sequence or expiry tracking. Hazardous jobs on plating lines or press pits get a safety-measures checklist printed on the job sheet, not a permit gate.
- Condition readings and meter data (vibration, run-hours, cycle counts) are entered manually, by photo-OCR, via WhatsApp, or through an API your plant sets up — there's no out-of-the-box poll of press PLCs or weld-cell counters.
None of this is a workaround for ISO-driven quality or safety programs — it's deliberately scoped to maintenance, which is what keeps the asset registry simple enough for operators to use without training.
Where OEE Fits on the Shop Floor
Press lines and weld cells are natural OEE candidates because throughput, not just uptime, is what customer audits and internal reviews usually ask about. AssetAI computes OEE — availability × performance × quality — per asset and per line from production logs, then ranks lines worst-first so a maintenance planner knows which weld cell or press to prioritize without first building a spreadsheet. It's the same TPM logic most auto-component plants already report against, just computed automatically instead of manually reconciled at month-end. See how it lines up against your current reporting on a demo, or browse other industries AssetAI is deployed in.
Getting a die jam or plating-tank leak logged the moment it happens — without adding a login screen to the shop floor — is often the harder half of the problem, and it's where most spreadsheet-based maintenance efforts quietly fail.
Getting Breakdown Data That Actually Explains a Failure
An operator standing next to a stalled press doesn't have time to open an app, find the right menu and pick from a list of assets. AssetAI's breakdown maintenance flow is built around that reality: the operator scans the QR code fixed to the machine, types their name and a scan PIN, and the work order is created against that exact asset — no separate login, no app to install.
What makes the resulting data usable later is what happens at the other end. A breakdown or corrective work order is hard-blocked from closing until someone records the failure mode, cause and remedy. That single rule is what turns months of work orders into a real failure Pareto by cause — rather than a pile of "fixed it" notes that nobody can analyze when a customer audit asks why a weld cell keeps going down.
- No login or app for operators reporting a fault
- Mandatory failure mode / cause / remedy before a WO closes
- Failure Pareto by cause available once enough work orders are closed this way
One Schedule Form for Presses, Compressors and Plating Tanks
Auto-component plants run three different maintenance philosophies on three different asset types, and juggling them in separate systems is a common source of missed PMs. A die needs servicing on a calendar; a compressor needs attention based on run-hours; a rotating shaft benefits from vibration readings before it fails outright. AssetAI covers all three from one schedule form — time-based, usage/meter-based and condition-based — rather than forcing plants onto a purely calendar-driven plan, which is closer to the logic behind total productive maintenance than a simple date-triggered PM list.
- Time-based PM for die servicing on a fixed interval
- Usage/meter PM for compressor run-hours or weld-gun cycle counts
- Condition-based PM for vibration checks on rotating equipment
PM compliance sits on the standard 30-day dashboard as one of four fixed KPIs, with MTTR, MTBF and availability available in Analytics for anyone digging deeper — useful context if you're still building out what a CMMS should be tracking in the first place.
Rolling This Out on a Live Shop Floor
Most auto-component plants already have dozens of machines, several vintages of compressors and plating equipment with mixed AMC and warranty status — introducing a CMMS mid-stream means the asset registry has to absorb that mess on day one, not after a clean slate. AssetAI's asset registry holds commercial, warranty and AMC data on one record per asset, and coverage status on compressors or plating pumps is derived automatically using a fixed precedence — warranty, then AMC, then expired, then none — so nobody has to manually track which contract applies before raising a work order.
Plants weighing this against ISO-aligned maintenance practice, covered in general terms on ISO's standards library, or comparing against sector data from IBEF's industry reports, can see how AssetAI's use cases and pricing line up before committing — and a walkthrough on your own asset list is available through a demo.
CMMS for Auto Component Plants FAQs
How do I set up preventive maintenance for different equipment like presses, compressors and weld cells on the same platform?
AssetAI uses a single schedule form that handles time-based PM (like die servicing every 500 hours), usage-based PM (compressor run-hours or weld-gun cycles), and condition-based PM (vibration alerts on rotating equipment) all together. You enter each machine—press, compressor, weld cell—as an asset with its own record including warranty and AMC details, then assign the PM frequency type that fits. The system tracks compliance across all equipment types in one unified view, making it easy to see which machines are due and which are overdue, without switching between different tools or spreadsheets.
Our dies and weld guns fail often but we don't know if it's the same root cause. How does CMMS help us find the pattern?
Every breakdown work order in AssetAI is hard-blocked from closing until the technician enters the failure mode, root cause, and remedy applied. This forces consistency in how failures are recorded so you can build a real Pareto by cause—not just a list of incidents. Over time, you'll see if die jams are from operator technique, fixture wear, or material variation, and whether weld faults come from electrode degradation or joint design. You can then target preventive maintenance improvements where they'll have the most impact.
Can operators report machine problems without logging in or using an app?
Yes. An operator can scan a QR code attached to the machine, enter their name and a PIN, and report a breakdown directly—no login, no app download needed. This lowers the barrier to reporting, so issues reach maintenance faster and downtime data is captured in real time. The work order lands in AssetAI with the asset and operator already identified.
We have presses with dies, weld cells with guns and fixtures—can I organize all these parts under their parent machines?
AssetAI lets you build a five-level asset tree: Equipment (top level, like a press), Assembly, Sub-Assembly, Component, and Part. Dies, fixtures, weld guns and jigs become child assets linked to their parent press or weld cell. This way you can track maintenance, warranty and service history for individual components while keeping them logically grouped under the machine they belong to, making it simple to find what needs work and understand the full asset structure.
How do I know which press or weld line is slowing down production the most?
AssetAI calculates OEE (Overall Equipment Effectiveness) per asset and production line by combining availability, performance, and quality data from your production logs. The system ranks machines worst-first, so the press or weld cell with the lowest OEE appears at the top. This tells you which equipment is losing the most throughput to downtime, slow cycles, or scrap, guiding you to focus preventive maintenance and root-cause work where it will protect output. You can explore deeper MTTR, MTBF and availability metrics in Analytics.
Our compressor and plating pump are under warranty and AMC—how does the system know which one applies?
AssetAI automatically derives warranty and AMC coverage from the asset record using a fixed precedence: warranty coverage applies first, then AMC if warranty has expired, then expired coverage, then none. When a corrective or PM work order is created on a covered asset, the system knows the correct coverage type and can help route the request to the right vendor or internal team. This removes manual checking and ensures compliance with contract terms.
We run three shifts and presses break down at different times. How do I track downtime accurately across all shifts to know which one has the worst equipment reliability?
AssetAI logs every maintenance event with exact timestamps and duration. Filter downtime reports by shift, equipment, and date range to identify patterns. You'll see which shift reports more breakdowns and whether it's operator error, load issues, or worn tooling. This helps you plan preventive work during low-production windows or allocate resources better. See maintenance analytics for real-time dashboards.