QAS ARC Weld Monitor

WeldQAS is an automatic monitor, controller and recorder for the arc welding ( MIG/MAG, TIG, submerged arc welding, plasma jet welding etc.)

KEY BENEFITS:

  • it allows automatic welding supervision
  • it works on the bases of the recording of the welding parameters during welding, without any changing to the welding torch head
  • it is based on a new technology of digital high-resolution data recording and intelligent process data computing in a signal processor (ASP – Advanced Signal Processing),and
  • it allows a substantially improvement and detection of welding faults

The three main impacts in a manufacturing environment for the arc monitoring system are:
1. Supervise: 100% monitoring and validation of the engineered weld programs and procedures during production. At this level the system prevents defective welds due to disturbances, faulty equipment operation or un authorized interference.
2. Detect: With the 50KHz frequency, quick fault detection and even intermittent faults can be detected and flagged as suspect or clearly marked as faulty. This is made possible by using the arc as the quality sensor
3. Document: Each and every weld through the production for each weldment is captured and recorded. As a result, robust archiving of the manufacturing data for the entire life span is achieved.

FEATURES:

Model µQAS QAS-V5
Display 6 “ TFT active 12 “ TFT active
Ring buffer 10,000 weld seams 20,000 weld seams
Monitors Single or dual weld torch Single or dual weld torch

• Advanced Signal Processing(ASP)
    o Changes in the welding arc are reflected in the welding parameters, monitored every 0.00002 seconds.
• Comparison of real values against SPC curves configured as threshold or envelope curves with (LLL, LL, NV, UL, UUL) regions
    o The natural fluctuations or divergences which do not impact welding product stability are filtered out, therefore trends can be recognized easily.
• Summary of stability via a quality mark (1-5) which associates to IO and alarms
• Automatic statistical learning
    o The signals are evaluated statically and abnormal behavior is excluded automatically.


The monitoring limits (faults) were learned from the course of many welds automatically.

• Documentation, Statistics and Optimization
    o Each record has a time stamp, which equipment, part ID, welding parameters being monitored, monitoring results.
    o Stored in a relational database on a network for archiving and company wide access for reporting.


Statistical representation

• Creation of Weld Jobs
    o All welded seams for a station are created as a job and the results of the job combined
    o Makes it possible the immediate combination of results of the job for:
        • The executed weld numbers
        • Problems of the quality of individual welds
        • Weld cycle time