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    aRTi-D™ Quality, Quality Control

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    Quality control that leads to immediate detection — without human subjectivity
    SEEMS integrates machine vision directly into production, detecting deviations as they occur — not after the fact.
    Automated machine vision inspection
    Instant detection of deviations
    Documented quality in real time
    // 01 — THE PROBLEM

    Why traditional quality control is not enough

    In heavy and continuous manufacturing, quality control still relies on sampling, visual inspection by humans, and offline recording.
    70–80%
    of defects are detected
    by operators, and accuracy drops by 15–25% after 2 hours of continuous inspection
    +40–60%

    more defects

    are detected by automated machine vision compared to manual inspection
    ~20%

    of revenue is lost

    to the cost of poor quality — scrap, rework, returns, production downtime

    TYPICAL SCENARIO

    The deviation was detected during the final inspection. The night shift had already produced 800 non-conforming units.”
    Result: increased scrap, rework, and delivery delays.
    // 02 — THE APPROACH

    What makes SEEMS different

    SEEMS automates quality control using machine vision and its own software, designed for industrial environments with continuous production.
    01

    Image capture

    Directly from the production line, in real time
    02
    Edge analysis
    Processing at the point of production — without cloud delays
    03
    Instant detection
    Identifying deviations the moment they occur
    Automated testing complements existing quality control mechanisms—it does not replace them.
    // 03 — FEATURES

    What it offers in practice

    AUTOMATED VISUAL QUALITY INSPECTION
    Automated quality control using machine vision
    Continuous 24/7 monitoring of products or processes
    Detection of deviations as soon as they occur — regardless of shift or operator
    DEVIATION, DOCUMENTATION, AND ACTION
     Automatic recording of quality deviations
    Correlation of deviations with orders, stages, and time
    A foundation for immediate response and evidence-based management
    TRACEABILITY & QUALITY ANALYSIS
    Complete history of inspections and deviations
    Comparable quality data over time
    Support for reviews and continuous improvement
    APPROVALS & QUALITY WORKFLOWS (OPTIONAL)
    Workflows for handling deviations and actions
    Integration check before closing cases
    They are activated only when needed—they do not interfere with daily operations.
    // 04 BENEFITS
    What you actually gain
    Immediate detection of deviations
    Deviations are detected the moment they occur—not during the final inspection.
    Consistent and objective inspection
    The same criteria 24/7—regardless of shift, operator, or fatigue.
    Reduction of scrap and recurring issues
    Timely intervention before the deviation affects the entire batch.
    Complete quality documentation
    Every inspection is recorded and linked to actual production.
    → Quality control is transformed from a piecemeal process into an automated mechanism for prevention and improvement.
    // 05 — CUSTOMIZATION
    Designed for demanding industrial environments
    SEEMS' Automated Quality Control adapts to the logic of the production process, supporting inspections in demanding continuous-operation environments.
    // 06 — INTEGRATED PLATFORM
    Part of the SEEMS unified platform
    Automated Quality Control integrates with the other modules.
    Quality Control — quality linked to production
    CONNECTED TO
    PO Tracking
    Link deviations to orders and production stages.
    Production Analytics(OEE)
    Correlate quality with performance and production losses.
    Digital Forms
    Supplementary documentation of deviations and actions.
    Predictive Maintenance
    Support for root cause analysis and predictive intervention.
    Quality is integrated into a unified production view—with data from across the entire platform.
    From visual inspection to automated quality control
    MANUAL INSPECTION
    Relies on data, machine vision, and real-time processing.
    SEEMS
    Relies on data, machine vision, and real-time processing.