The Challenge
PERODUA, Malaysia's leading automotive manufacturer producing over 350,000 vehicles annually, faced critical quality control challenges in their lighting system verification process:
- Manual Inspection Bottlenecks: Quality control teams were manually inspecting every vehicle's lighting system, creating production delays and inconsistent results.
- Human Error Risk: Visual fatigue from repetitive inspections led to a 2-3% error rate in detecting faulty installations or non-functioning lights.
- Production Line Speed: Manual checks limited line speed to 60 vehicles per hour, below the target of 100 vehicles per hour.
- Compliance Pressure: Stringent automotive safety regulations required 100% verification of all lighting systems with documented proof.
- Cost Inefficiencies: Large QC teams and rework costs were impacting operational margins.
"Safety is our top priority at PERODUA. We needed a solution that could guarantee 100% accuracy in detecting lighting defects while maintaining our production efficiency. Manual inspection was no longer sustainable."
- Dato' Zainal Abidin Ahmad, President & CEO of PERODUA
Key Takeaways
- Computer vision can achieve near-perfect accuracy in automotive quality control
- Edge computing ensures real-time processing without production delays
- AI implementation can improve both quality and production speed simultaneously
- Proper change management and training are crucial for successful adoption
- Data from AI systems provides valuable insights for continuous improvement
What Our Client Says
Fylix AI's solution has elevated our quality control to world-class standards. The accuracy and speed are remarkable, but what impresses me most is how it has empowered our teams with data-driven insights.