How Shriji Enhanced Pharma Bottle Cap Quality with Jidoka’s AI-Powered Smart Inspection
Using Jidoka’s AiI Visual Inspection Systems, Shriji Enhanced Pharma automated defect detection for bottle caps on its wad assembly line
achieving real-time inspection speeds of 800+ parts per minute, reducing scrap, rework costs by over $10,000 annually.
OVERVIEW
Shriji Enhanced Pharma is a global leader in pharma-grade plastic packaging solutions, manufacturing high-precision bottle caps that demand
stringent visual quality standards. Each cap must be free from surface anomalies and assembly defects to ensure sealing
integrity and pharmaceutical compliance.
However, with over 1 million bottle caps to inspect daily, manual or semi-automated inspection methods struggled to maintain both throughput
and consistency. Delayed defect feedback led to unnecessary rework and high rejection rates. Shriji needed a high-speed, reliable, and traceable
inspection system capable of handling massive production volumes without slowing down the line.
THE OPPORTUNITY
Manual inspection and legacy systems couldn’t keep pace with Shriji’s high-volume bottle cap production:
- Over 1 million caps produced dailymade 100% manual inspection impractical.
- Minute defects such as sealing damage, contamination, or surface irregularities often went undetected.
- Delayed feedback on rejections led to higher scrap, rework, and wasted production time.
- Even a small batch of undetected defects could result in costly product rejections and customer dissatisfaction.
JIDOKA’S APPROACH
- High-Speed Single-Camera Inspection Architecture
A single high-resolution top camera captures both the top and inner surfaces of each bottle cap as they move on Shriji’s existing conveyor automation line.
- EdgeAI–Enabled Defect Detection
Jidoka’s proprietary Kompassdeep-learning engine runs inference on captured images in less than 100 milliseconds, identifying and classifying defects in real time with high precision.
- Automated Decision and Ejection
The system delivers immediate OK/NG decisions, directly linked to an automatic pneumatic rejection mechanism that removes defective caps from the line instantly eliminating lag between detection and response.
- Smart Traceability and Alerts
Each inspection result is logged and visualized on a digital dashboard. Operator alerts notify of recurring defect trends, enabling proactive maintenance and data-driven process improvement.
A single high-resolution top camera captures both the top and inner surfaces of each bottle cap as they move on Shriji’s existing conveyor automation line.
Jidoka’s proprietary Kompassdeep-learning engine runs inference on captured images in less than 100 milliseconds, identifying and classifying defects in real time with high precision.
The system delivers immediate OK/NG decisions, directly linked to an automatic pneumatic rejection mechanism that removes defective caps from the line instantly eliminating lag between detection and response.
Each inspection result is logged and visualized on a digital dashboard. Operator alerts notify of recurring defect trends, enabling proactive maintenance and data-driven process improvement.
Results 1
Results 2
THE BIG WIN
Major Outcomes for Shriji
800+ Parts/Minute
800+ Parts/Minute
Achievedhigh-speed inspection without throughput loss.
10% Reduction in Defect Occurrence
Continuous feedback loop drives improvement.
$10K Annual Cost Savings
$10K Annual Cost Savings
Reduced rework and scrap losses.
ROI Achieved in 18 Months
ROI Achieved in 18 Months
Fastpayback through efficiency and quality gains.
Get in Touch with us about this Testimonial
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