Zero Defect Quality Management System Using AI for Automotive Manufacturing
The client is a leading automotive manufacturer, operating multiple high-volume production plants. With expanding production lines and advanced AI-driven inspection systems, they required a centralized digital platform to standardize quality processes, improve traceability, and support enterprise-wide zero-defect initiatives across all plants.
The client’s AI vision inspection data was stored in local plant systems, creating several operational challenges:
No unified quality platform across multiple plants
Fragmented PLC and camera data, making traceability time-consuming
Slower decision-making due to the absence of centralized dashboards
Manual errors while mapping AI results, images, and PLC logs
Limited visibility into OK/NG performance for managers and line supervisors
High rework cost due to delayed defect identification
The lack of a consolidated view directly impacted production efficiency, defect tracking, and overall quality assurance.
The client wanted a next-generation, factory-wide quality management solution built on Mendix with the following goals
Create a centralized platform for all AI vision inspection data
Enable VIN-based traceability with sub-second response time (<0.5 sec)
Automate mapping of PLC data, camera results, and inspection images
Provide real-time dashboards showing OK/NG status, accuracy %, top defects, etc.
Reduce manual rework effort by 30–40%
Enable role-based access for Admin, Manager, Line Supervisor, and Operator roles
Support future scalability for additional cameras and new plants
MXTechies designed and delivered a Mendix-based Zero Defect Overflow System with a fully automated inspection data flow
● Integrated PLC systems via OPC UA using REST services
● Captured AI vision results and camera outputs in real time
● Each VIN is mapped with a unique vehicle ID and engine ID
● Images fetched automatically from FTP
● Image filenames matched using timestamps and PLC IDs
● Operators could manually upload Stage 3 & 4 images
● OK/NG analytics, rework percentage, defect trends
● Top 10 recurring defects and the last 10 defects
● Camera-wise, line-wise, and station-wise performance
VIN-level search displaying:
● Model – Checkpoints – Inspection results – Camera images – Timestamped PLC logs
● 4 user roles: Admin (full control), Manager (plant analytics), Line Supervisor (line insights), Operator (inspections & uploads)
● AD-based SSO using corporate authentication
● Data encrypted at rest and in transit
Processed 100% of PLC data logs into Mendix with automated mapping
Achieved 0.2 – 0.5 sec response time for VIN retrieval
Integrated multiple cameras per station, ensuring sequential VIN flow
Configured 25+ master data entities (Plant, Line, Station, Camera, Model, Shift, etc.)
Built real-time charts: weekly, monthly, yearly, and custom ranges
Enabled export-to-Excel for all inspection and PLC data
Developed an end-to-end traceability workflow with historical snapshots
After implementation, MSIL achieved measurable operational improvements
Faster Defect Identification
Real-time insights sped up quality checks
Accurate VIN-to-Image Mapping
Automated mapping eliminated errors
Reduced Rework Cycle
Faster analysis for managers and supervisors
Centralized Inspection Data
All plants connected in one system
Improved Production Visibility
Better line planning and resource use
Faster Reporting
Instant Excel exports replaced manual reports
All inspections are managed in a single Mendix system
AI and PLC-driven inspections with real-time insights
Enterprise SSO, role-based access, and audit trails