We worked closely with an automobile manufacturer to replace manual inspection with a smarter, faster, and more reliable AI-powered vision system — engineered, installed, and commissioned by Techasoft. Four HD cameras, deep learning on NVIDIA GPUs, and ~32 inspection points per vehicle, with image evidence for every decision.
Multi-angle synchronized body image capture
Simultaneous part presence, orientation & defect checks
Instantaneous Pass or Hold automated line decisions
Tamper-proof photographic audit trail for every call
We identified the weak points in the manufacturer's existing manual inspection process: results depend on the operator, variants and optional parts are easy to mix up, and there is little proof on record when something is questioned.
Results change from one operator and shift to the next due to fatigue.
Dozens of models and option packs make mismatches easy to overlook.
Without images and timestamps, quality audits & warranty disputes stall.
Time is lost between manually inspecting a vehicle and deciding its fate.
High-resolution HD cameras capture detailed images of each vehicle during production. The images travel over network switches to a high-performance PC, where our deep-learning software analyses them on an NVIDIA-powered graphics system.
Captures multi-angle detailed images of vehicle components during production.
High-bandwidth switches move uncompressed frames to edge PC over plant network.
Industrial edge computer equipped with NVIDIA GPUs runs deep learning models.
Detects, classifies, segments, and analyzes components and surface defects.
Automated Pass or Hold line decision, backed by timestamped image evidence.
A robust, industrial-grade architecture bridges optical hardware with plant execution systems. The solution ingests vehicle VIN data directly from plant MES/ERP, matches it against real-time Bill of Materials (BoM), and outputs verified verdicts without slowing the production conveyor.
| Vision Hardware | Industrial GigE cameras with controlled illumination tunnel |
| Edge Compute | Industrial PC with high-performance NVIDIA Tensor Core GPUs |
| Deep Learning | YOLO object detection, convolutional neural networks, OCR |
| Integration | Barcode/VIN scanners, MES & BoM REST APIs, PLC triggers |
| Quality Insights | Centralized PDI web dashboard, audit database, and defect reports |
The solution starts with a full AI training phase. Sample images of acceptable and defective components are given to the system, so it learns to identify, analyse, classify and detect defects while allowing for the natural variation of manufacturing.
Feed high volumes of good and defective component sample images into the model.
Run deep neural network models on real-time production line image feeds.
Compare every AI decision against manual inspection ground truth to measure confidence.
Improve and retrain the edge model with edge cases to continuously boost accuracy.
Once deployed, the system inspects each vehicle automatically and flags anomalies and defects in real time. Four high-resolution cameras are integrated into the line and capture multiple views of the vehicle body.
The software performs approximately 32 inspection points around each vehicle, verifying component specifications, alignment, and defects without significantly slowing down line throughput.
End-of-line vehicle inspection. Every vehicle at the station is captured on camera, and the system locates each fitted part, identifies the exact variant and flags anything missing or wrong.
An intelligent, automated sequence ensuring zero defect escapes to dispatch.
Model and variant data are pulled automatically from production scheduling, VIN barcode/RFID scans, or MES APIs. The system immediately loads the exact Bill of Materials (BoM) checklist for that specific vehicle.
Multiple industrial cameras stationed in the inspection tunnel capture synchronized internal and external views. Deep learning models detect component presence, orientation, color, and fitment against the loaded BoM.
Configured confidence thresholds and manufacturing tolerance rules judge the findings in real time. Any component mismatch or omission flags the vehicle and routes it to an exception bay for human review.
Verified inspection results, including timestamped high-resolution image evidence of every angle, are stored securely in audit databases, accessible instantly through central PDI dashboards.
Deep learning lets the system recognise defects while accepting natural manufacturing variation.
Inspection cycle time is significantly reduced, accelerating line throughput without human fatigue bottlenecks.
Defects and component mismatches are caught with 100% uniformity across every operator shift and vehicle variant.
Permanent photographic proof for every decision and exception, forming a reliable basis for continuous process improvement.
Infinitely searchable digital records indexed by VIN for hassle-free quality reporting, customer audits, and warranty tracking.
From the first consultation to commissioning, Techasoft delivered the complete solution tailored to the customer's manufacturing line.
Understanding factory needs
Inspection scope defined
Development & training
Custom edge programming
Line & MES systems
Rigged on plant floor
Testing and go-live
"We are proud to have delivered a robust and innovative AI-powered inspection system that helps the manufacturer improve quality control, inspection efficiency and production productivity."
Share your vehicle inspection goals and line specifications with us, and we will shape a customized vision automation proposal for your assembly operations.
