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Optical
Quality control with AI -
The future of the industry

Visual inspection as a decisive success factor in industrial production

Optical quality control (OQC) comprises targeted visual inspection processes that ensure products are free from defects and comply with defined quality standards. By planning, documenting, monitoring and optimizing visual inspections along the entire value chain, processing companies can ensure a high level of process reliability. In order to comply with norms, regulations and quality management standards (ISO 9001), visual quality control forms the basis for defect-free products, sustainable competitiveness and maximum customer satisfaction.
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36ZERO Vision significantly expands this approach. The use of modern deep learning technologies automates quality assurance, making it both more intelligent and more precise.

While conventional technologies often interpret deviations as defects, the AI-based solution from 36ZERO Vision recognizes the difference between actual defect patterns and non-critical anomalies. This avoids pseudo defects and significantly increases the efficiency of visual quality inspection.

Artificial intelligence analyzes production images in real time, clearly classifies identified errors and thus enables targeted control of production processes. This supports employees and contributes to the continuous improvement of production processes.

One particular advantage is its flexibility: thanks to the no-code self-service platform, users can train the AI independently. Just a few sample images are enough to adapt the system to new products, variants or series. The models run autonomously on-premise, are hardware-independent and integrate seamlessly into existing optical quality control methods.

In this way, 36ZERO Vision creates a new form of visual inspection - precise, efficient and future-proof. Companies benefit from reduced waste, more stable processes and a sustainable improvement in their quality standards.

Boundaries of conventional methods
in your production

Traditional inspections detect anomalies based on machine learning and statistical methods, but cannot clearly classify errors.
This leads to pseudo errors, rejects and unnecessary inspection processes.
Manual quality checks are resource-intensive, error-prone and slow down processes.

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36ZERO Vision:
AI-based Quality control
in industry.

AI-supported
image analysis in real time

  • Deep learning models identify error patterns and completeness at pixel level.
  • Pseudo faults are eliminated and the accuracy of the visual inspection is increased.
  • Reading QR codes and plain text.
36zero Vision Plattform Anwendung 3 Schritte 01 Bilder hochladen

Reliable testing of error patterns

Error types are categorized clearly and at an early stage. This leads to greater added value:
  • Higher efficiency of production processes.
  • Optimal decision-making basis for subsequent production steps.
  • Traceability and containment of recalls Improved customer satisfaction.

No-Code
Self-service
platform

  • Cloud platform: AI training directly by the user.
  • 5-25 sample images per error type.
  • Flexible adaptation to new products and variants.
36zero Vision Plattform Anwendung 3 Schritte 03 Integration

On-Premise
execution

  • Local inference on existing systems.
  • Hardware-independent, compatible with all common industrial cameras.
  • Ideal for retrofitting and company-wide standardization.
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Visual quality assurance in the context of the Quality management (ISO 9001)

36ZERO Vision complements existing quality management systems:

  • Quality planning:
    Definition of the relevant test characteristics and quality requirements
  • Quality control:
    AI-supported process monitoring and automatic corrections
  • Quality control:
    Objective analysis of known error patterns
  • Documentation:
    Automatic and transparent traceability through data archiving
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Automated quality assurance as competitive advantage

With 36ZERO Vision, quality assurance is transformed from a reactive control process into a proactive success factor:
  • 1 // Best-in-class error detection: Data-centric, supervised AI model reliably classifies even complex error patterns.
  • 2 // No-code self-service: No programming or AI knowledge required.
  • 3 // Hardware-agnostic & scalable: Flexible use in new and existing infrastructure (greenfield & retrofit).
  • 4 // Fast & efficient: Typically only 5-25 training images and 2 hours effort for a productive model, analysis speed 20 ms. or faster.
  • 5 // Eliminate pseudo errors: Faultless products to reduce material and production costs and ensure efficient use of resources.
  • 6 // Transparency instead of a black box: Full access to the logic, customizable at any time at no additional cost.
  • 7 // Standardized interfaces: Smooth integration with renowned, world-leading partners.
  • 8 // Process added value: Fault pattern recognition provides valuable insights for the continuous improvement of product quality and production processes.
Use the competitive advantages of AI!

36ZERO Vision - for quality that sets standards and Ensures competitiveness.

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