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- Pharmaceutical industry & medical technology

More security for patients, Fewer risks for manufacturers - with AI-supported, optical quality control.

The use of state-of-the-art AI algorithms for quality assurance is crucial for manufacturers of medical technology as well as medical and pharmaceutical products. the balance between patient safety, guidelines and economic efficiency find. Despite increasing product complexity, a comprehensive, reliable and Reproducible quality assurance be ensured.

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AI classifies and documents errors - in cycle time, in series, in the highest quality

Medical, medical technology and pharmaceutical products are subject to the strictest regulatory and legal requirements (GMP, FDA, EMA) and have a zero-defect tolerance in terms of product safety. Even the smallest visual deviations - from particles in liquids to damaged blister packs - can have serious consequences: Production stops, product recalls and loss of confidence among patients and authorities.

People's health is at stake.

Artificial intelligence (AI) is revolutionizing visual quality control: automated image processing systems inspect each unit in real time, detect deviations that would escape the human eye and deliver consistently classified and documented results. This not only detects errors, but also identifies patterns that allow conclusions to be drawn about process optimization and therefore greater efficiency.

36ZERO Vision brings deep learning to automated series production.

The cloud platform is used to develop AI models individually for each application. It is initially trained with known defect types and can be continuously improved through interaction with employees. It adapts flexibly to new product variants, applications and production conditions and standardizes quality decisions worldwide.

Images from industrial cameras are analyzed autonomously, on-premise and in real time using the trained models, error patterns are detected and products are objectively evaluated. Surfaces, packaging, accuracy of fit and completeness can be checked without delay - faster and more precisely than by the human eye or traditional inspection systems such as anomaly detection, which declare any deviation as a defect.

The
Result:

  • Are errors classified, causes can be eliminated and processes stabilizedthus increasing the Quality, compliance and efficiencywhile Costs, risks and regulatory problems sink.

Typical errors on pharmaceutical and medical products

1. pharmaceutical industry 

  • Spots, dots or inclusions on medicines, tablets, capsules or blisters
  • Damaged surfaces (cracks, flaking, broken edges)
  • Incorrect embossing / missing marking on tablets
  • Particles in the product or in liquids (visible foreign bodies or glass particles)
  • Faulty blister packaging (Tablet missing, wrong compartment sealed, seal seam damaged)
  • Labeling errors (crooked, wrong, incomplete, double)

2. medical devices

  • Air pockets or bubbles in transparent components (e.g. syringes, catheters)
  • Unclean welded or glued seams (for tubes, bags or films)
  • Packaging errors (Sealing seams not tight, films torn, incorrect sterile barrier)
  • Foreign bodies or fibers in sterile packaging or on products
  • Missing or incorrect markings (e.g. scales on syringes or tubes)

3. medical technology 

  • Surface defects (scratches, cracks, fractures, polishing defects on metal instruments)
  • Coating defects (e.g. flaking of coated surgical tools or implants)
  • Deformations for plastic or metal parts
  • Inadequate accuracy of fit  (visible gaps, loose parts)
  • Incomplete or incorrect labeling (UDI codes, batch numbers, CE marking)
filling_correct
Each blister is filled correctly.
punching errors
The perforation is uneven, which indicates insufficient tool sharpness or faulty punching guidance.
defective_packaging
The blister is damaged or torn, caused by mechanical stress or improper handling during the packaging process.

Challenges

  • Strict regulations → Companies must adhere to the highest standards.
  • Complex documentation & traceability → Every error, every deviation and every corrective measure must be fully documented.
  • High audit pressure → Authorities and notified bodies check regularly and expect full compliance.
  • Diverse products → From tablets and catheters to complex surgical instruments, each product group has its own error patterns.
  • Subjectivity during manual inspection → A shortage of skilled workers makes it difficult to maintain consistently high quality.
  • Training costs → Employees must be regularly trained in GMP, ISO and testing techniques.
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advantages

  • Objective error classification creates uniformity between production, QA and technology.
  • Process improvement through root cause analysis ensures stable, efficient processes.
  • Automation is made possible, as pseudo errors and manual reworking are eliminated.
  • Regulatory security thanks to GMP/ISO conformity, clear error classification and closed-loop documentation.
  • Higher productivity with less waste, downtime and use of resources.
  • Fewer complaints & recalls reduce costs and safeguard reputation.
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Applications

1. pharmaceutical industry

  • Medication, tablet & capsule inspection: Detection of breakage, missing embossing and foreign particles.

  • Blister control: Automated image analysis checks completeness, sealing seams and correct placement of each unit.

  • Serialization, label & packaging inspection: Checking batch numbers, expiration dates, UDI codes for completeness and legibility.
  • Inline anomaly detection: Analysis of subtle error patterns in production before errors even become visible.

2. medical devices

  • Surface testing of plastics & metals: Detection of micro-cracks, scratches, bubbles or material inclusions.
  • Seam & weld inspection: Deep learning analysis of welded and glued seams (e.g. on catheters or tubes) for tightness and cleanliness.
  • Transparency and bubble test: Inspection of transparent parts (syringes, catheters) for air pockets or foreign bodies.
  • Packaging integrity: Inspection of films and sealing seams for perforation and manupulation to ensure sterility.

3. medical technology

  • Instrument testing: Detection of polishing defects, corrosion, loose particles or burrs on surgical tools.
  • Accuracy of fit & assembly control: Inspection of gap dimensions and geometries in assemblies.
  • Predictive Quality Monitoring: Linking image data with process parameters

The most important Questions
at a glance:

How does AI-based visual quality inspection support GMP-compliant automated inspection in pharmaceutical manufacturing?

36ZERO Vision automates visual quality inspections in GMP-regulated pharmaceutical manufacturing and detects critical defects such as particle contamination, packaging defects, or labeling errors with high robustness and consistent decision-making logic. This automated, objective classification reduces the variability inherent in manual visual inspections—studies show that the human detection rate typically ranges from 60 to 80 %—and improves process reliability in GMP environments. Each inspection process is documented in an audit-proof manner with a timestamp, component identification, and the basis for the decision—a fundamental requirement for pharmaceutical audit trail standards.

What pharma-specific quality defects can AI-based visual quality inspection detect in medical and pharmaceutical production?

36ZERO Vision detects and classifies, among others, the following defect types in pharmaceutical and medical device manufacturing processes: particle contamination in primary packaging (vials, ampoules, pre-filled syringes); cracks, micro-cracks, and deformations in glass and plastic housings; improper seals and damage to blister packs and foil seals; printing errors, misplacements, and color deviations on labels and package inserts; as well as color deviations and damage on tablets, capsules, and implants. The integrated OCR function additionally enables automated verification of batch numbers, expiry dates, and serialization codes – for example, according to EU FMD (Falsified Medicines Directive) or DSCSA.

Does AI-based visual quality inspection meet the requirements for data security, GDPR compliance, and ISO 27001 certification in the pharmaceutical industry?

36ZERO Vision is certified according to ISO/IEC 27001:2022, the internationally recognized standard for information security management systems, and processes all production data in compliance with GDPR. The hybrid architecture separates cloud training and local edge inference, ensuring that production data and inspection images never leave the production environment during operation. This on-edge data retention is a crucial aspect for sensitive pharmaceutical data and trade secrets compared to purely cloud-based solutions. Images containing personal data can be automatically anonymized before storage.

A dedicated security and compliance team is available for detailed technical due diligence inquiries (security@36zerovision.com).

How consistent and reproducible is AI-based visual quality inspection compared to manual inspection in a GMP environment?

AI-based visual quality inspection has been shown to deliver more consistent and reproducible inspection results in a GMP environment than manual inspection: In controlled studies, human inspectors typically achieve detection rates of 60–80 %, which decline further over the course of the day due to fatigue and can vary significantly between inspectors and shifts. 36ZERO Vision supports employees with objective, consistent inspection decisions. This consistency is a fundamental prerequisite for robust process validations and process capability analyses (CPK) in accordance with GMP. The human-in-the-loop feedback system leverages the expertise of experienced quality staff for continuous model improvement, thereby freeing up quality personnel to focus on value-added activities.

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