Client Overview
A leading Tier-1 automotive component manufacturer based in Chennai, India, producing high-precision engine parts and assemblies for global automotive brands. With production lines running 24/7, the client needed to ensure flawless quality control while meeting strict deadlines and regulatory standards.
Our Approach
Our strategy focused on:
- Capturing defect samples to train deep learning models
- Integrating high-speed industrial cameras with AI-based processing units
- Implementing a scalable defect classification system
- Creating real-time rejection logs with image evidence for traceability
- Providing live dashboards for inspection results and batch quality
Challenge
The client relied heavily on manual inspection to detect surface defects, dimensional variances, and component alignment issues, which led to inconsistent results and high rejection rates from OEMs.
Machine Vision Automation
India
Key pain points included:
- Operator fatigue and inconsistent defect detection
- Slowed production speed due to visual inspection
- Lack of traceability for rejected components
- Frequent quality audits and rework penalties
- High cost of poor quality (COPQ) impacting profitability
Solutions Delivered
AI-Based Visual Inspection System
Deployed machine vision cameras integrated with AI models to detect scratches, dents, surface anomalies, and misalignments in under 0.5 seconds per unit.
Automated Rejection & Sorting Line
Integrated sorting mechanisms to separate faulty components automatically and tag them for rework or disposal.
Defect Classification Dashboard
Developed a real-time Power BI dashboard showing defect categories, frequency, and trends across shifts and lines.
Batch Traceability with Image Logs
Each rejected component was logged with a timestamp and defect image for quality audits and RCA (root cause analysis).
Technologies Used
Business Impact / Results
Qematic’s AI-powered machine vision system redefined the client’s quality assurance capabilities with:
What Our Clients Say
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Key Highlights (Summary Box)
| Metric | Before Implementation | After Implementation |
|---|---|---|
| Defect Detection Accuracy | 82% | 98.7% |
| Inspection Time per Unit | 1.5 sec | 0.5 sec |
| Human Errors in QC | High | Minimal |
| Rework/Audit Penalties | ₹7.2L/month | ₹3.5L/month |
| Traceability & RCA | Manual & limited | Automated & visual |
