Automotive · Assembly-line quality inspection
Defects that clear the line gate cost ten times more to fix than defects caught on it
Banao builds and deploys computer-vision inspection models on automotive assembly lines that check panel fit, weld points, fastener presence, and surface condition within cycle time — flagging or holding a unit at the station before it moves downstream.
The system runs on your existing line cameras where imaging conditions allow. Integration writes grades and reject flags directly into your PLC and MES, so every escape is logged, timestamped, and traceable to a VIN — without a supervisor needing to be present.
The first call is free · 45 minutes · no obligation
What we build
What a Banao assembly-line inspection system covers
Assembly-line quality inspection is not a single model — it is station-by-station coverage from body-in-white through trim-out, with each check wired into the stop-and-flag logic at that station.
Panel gap and flush measurement
Vision models that measure door, bonnet, and boot gaps against spec tolerance at the body-in-white stage — before trim makes rework expensive. Out-of-tolerance units get a logged flag, not a visual nod from an inspector who is on their eighth hour.
Weld-point and seam completeness
Models trained on weld images that check for missing, incomplete, or malformed spot welds and seam runs. Structural faults at this station that clear the line become warranty claims; caught here they become a three-minute repair.
Fastener and clip presence verification
Station-level cameras confirm fastener presence, orientation, and seating before the assembly moves to the next stage — eliminating the category of quality escape that shows up on a dealer repair order as 'missing bolt, loose trim panel'.
Body-panel surface defect detection
Defect models that flag dents, scratches, and surface irregularities on body panels and interior trim, graded against your acceptance criteria and logged per unit — not summarised into an end-of-shift count that hides which station produced them.
PLC and MES integration
Grades and reject flags write into your PLC and MES in real time. A reject holds the unit at the station and opens a traceable defect record — so warranty analysis months later can close the loop between an early-build fault and a field return.
Shift and line-trend dashboard
A single view of defect rate, miss rate by station, and defect correlation to raw-material batch or tool wear — so a systemic problem surfaces as it builds across a shift, not after an end-of-month audit.
Receipts
Where line vision is already running
Metrics shown dotted (··) are being finalised in our case-study metrics pack. Deployments are live; we publish numbers once verified.
Vision inspection added to existing line camera infrastructure
Banao applied computer-vision models to line and CCTV cameras already mounted over the assembly stations — adding an AI grading layer to the hardware already in place rather than re-cabling. The system flags and logs at the station within cycle time, with grades written to the existing MES.
Dogfooding
We run our own company on the AI we sell to yours
Banao operates a ~300-person engineering company on its own AI systems before any client sees them. InterviewGod screens every one of our own engineering hires. Vikaas runs our own demand-generation pipeline from end to end.
When we say a model is production-ready, it has already had to earn that rating in our own operation — where the cost of a miss lands on us, not on a client. That is a different standard from a vendor who has only ever demoed on a recording.
Screens Banao's own engineering hires, every week.
Runs Banao's own demand-gen pipeline end to end.
The honest version
When assembly-line vision inspection won't pay
Vision inspection earns its keep on high-volume, stable-process lines. It does not always earn its keep — and we would rather tell you before you commission a build:
- Low build volume: below a few hundred units a shift, a trained line inspector beats a vision installation on cost. We will say so in week one rather than quote a build you won't recover.
- High mix, frequent spec change: if your model mix and tolerance bands shift every few weeks, an inspection model built to current spec decays before it covers its cost. A different architecture suits this better, and we will design for it.
- Imaging that cannot be made consistent: if light levels, part orientation, or conveyor speed cannot be stabilised enough to frame a part the same way twice, week one is an imaging engineering problem — not always a modelling one, and sometimes the honest answer is not yet.
How we start
How we start — two weeks before any build decision
We examine your actual line, your hardest defect classes, and your existing cameras before quoting anything.
- 01
AI Discovery Sprint
2 weeks · fixed price
On-site at the plant. We audit imaging conditions at each station, test feasibility on your hardest defect classes with real part samples, and hand back a station-by-station inspection map, baseline accuracy projections, and a full ROI model — yours to keep whether or not you proceed. If you go ahead, the Sprint cost credits against the build.
- 02
Build
Data collection, labelling, and model training to your grading rules, then integration with line cameras, PLCs, and MES. The imaging rig and data pipeline are deliverables, not prerequisites you have to solve before we start.
- 03
Production and continuous learning
Edge deployment with operator override, a shift dashboard, and floor-team change management. Operator corrections feed back into the model on each shift's images — the system keeps improving on your specific line and your specific defect mix.
FAQ
Frequently asked questions
Can the system run on our existing line cameras?
Usually yes. Banao deploys on existing line and CCTV cameras where imaging geometry and lighting allow. The week-one audit establishes which stations can use existing hardware and where a camera upgrade is genuinely needed — we do not specify new hardware unless the imaging actually blocks accuracy.
How does a reject flag reach the line without slowing cycle time?
Inference runs edge-side, so the grading decision is available within cycle time at the station. The flag writes into the PLC and can trigger a conveyor hold or a light-stack alert depending on your line configuration. Integration with stop-and-hold logic is part of the build deliverable, not a follow-on project.
Our model mix changes frequently. Does that break the inspection model?
High mix is a real constraint that we design for explicitly. If tolerance bands and spec change every few weeks, we build the system with modular per-variant models or a parametric rule layer so inspection criteria can be updated without full retraining. We scope this in the Discovery Sprint.
How does line inspection close the loop to warranty claims?
Every defect decision is logged per unit with a station, timestamp, defect type, and image reference, written into the MES. Months later, when a warranty claim arrives, the inspection record for that VIN is queryable — so engineering can determine whether a fault was present at the line or introduced post-line, and close the feedback loop into the model.
What does the Discovery Sprint cost, and what do we get?
The Sprint is fixed-price and runs two weeks, with Banao on-site at the plant. You receive an imaging-feasibility assessment per station, model-accuracy projections on your hardest defect classes, a full ROI model, and a go or no-go recommendation per inspection point — yours to keep regardless of what you decide. If you continue to build, the Sprint cost credits against the engagement.
Get started
Bring your hardest defect class to our engineers
Show us your line cameras and your worst escapes. In 45 minutes we will tell you whether vision inspection is worth building on your line, and what it would take to get there.
Book a Discovery Sprint