Case Studies
Boosting Drill Bit Quality with AI-Powered Video Inspection
Client Overview
Industry: Manufacture
Solution: Tictag AI
A global leader in precision drill bits partnered with Tictag to enhance inspection accuracy and operational efficiency. Projected results include ~80% defect-level recall, ~66% frame-level recall, low false positives, and a faster automated inspection process. Read on to see how these outcomes were achieved and the full operational impact.
Illustration
Background
A global precision tool manufacturer produces high-quality drill bits for industrial applications. The company needed to maintain strict quality standards while improving inspection efficiency. Manual inspection processes were time-consuming, inconsistent, and struggled to reliably detect micro-defects, creating the need for a scalable AI-powered solution to ensure accuracy, traceability, and faster throughput.
Key Challenges
- Detect micro-defects in precision drill bits consistently
- Reduce time-consuming, labor-intensive manual inspections
- Handle diverse and complex defect types reliably
- Collect high-quality data for traceability and quality assurance
The Solutions
- AI-Powered Video Defect Detection: Analyse high-resolution 360° videos to identify anomalies on drill bits
- Human-in-the-Loop Validation: Leverage expert review and crowdsourced validation to continuously improve model accuracy
- Precision Imaging Hardware: High-resolution cameras with telecentric lenses, ring lights, and rotary stages capture drill bits at micron-level detail
- Dual-Track AI Architecture: Spatiotemporal and DETR-based models fuse outputs to maximise defect detection recall and reduce false positives
Implementation
High-resolution video feeds of drill bits are captured and split into 1-second clips. An initial AI model filters out defect-free frames to reduce processing load. The remaining frames are analysed by DETR and Mask2former segmentors. Clips are then fed into a lightweight spatiotemporal defect recognition model, and every frame with detected defects is processed by defect localizers to accurately identify and localize anomalies.
Result & Business Impact
- 80% defect recall at the defect level
- 66% recall at the frame level
- Faster automated inspection process, reducing manual labour
- Provides visual, frame-level outputs to aid human-in-the-loop verification
Conclusion
Tictag deployed its AI-powered visual inspection system to automate precision drill bit quality control while delivering comprehensive, actionable reports. The solution not only improves defect detection accuracy but also provides operational insights to optimise inspection workflows, supporting a scalable, Industry 4.0-ready manufacturing environment.
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