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How Diageo Achieved In-Process Labeling Precision With Jidoka
Industry
Alcoholic Beverages (Alco-Bev)
Result 1
99%+ accuracy in detecting label defects and text errors
Deployments
Kompass AI and Tigris (Modular Vision Hardware)
Result 2
Faster, more reliable in-process inspection with automated ejection and alerts
By deploying Jidoka’s AI-driven inspection systems, Diageo streamlined its label verification(LBI/Fill level) process at 300 bottles per minute, ensuring accurate text, proper orientation, and accurate label – while minimizing manual oversight.
Overview
Diageo is a global leader in premium spirits, producing iconic brands across more than 180 countries. Known for high-volume bottling lines, Diageo needed a robust, automated solution to ensure precise labeling – both for compliance and brand consistency – without slowing production.
The Opportunity
At Diageo, manual label inspection was error-prone and unsustainable at high speeds:
- 300 bottles/minute demanded real-time verification of text, logos, barcodes, and label orientation.
- Bottles with torn, scuffed, or bubbled labels could slip through, risking brand image and regulatory non-compliance.
- Pre-printed and variable text needed accurate reading and matching against templates—human oversight alone wasn’t enough.
Jidoka installed Kompass and Tigris to tackle Diageo’s labeling challenges:
1. Real-Time OCR & Object Detection
- High-resolution cameras captured label regions, reading critical text (brand names, disclaimers, barcodes) in milliseconds.
- Object detection verified logo presence, correct orientation, and consistent label placement.
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2. Defect Identification & Classification
- Automated detection of label tears, trapped bubbles, and scuff marks, triggering immediate alerts.
- Any misprint or mismatch from the approved template was flagged for rejection.
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3. In-Process Inspection & Ejection
- Jidoka’s hardware module, Tigris, seamlessly integrated with Diageo’s bottling lines, ejecting faulty bottles on the fly.
- An andon-like alert system informed operators of recurring issues, speeding up root-cause analysis.
4. Adaptable for Multiple SKUs
- The AI-driven approach allowed quick configuration changes for new label designs, compliance requirements, or product variations.