Advanced Welding Processes: Technologies and Process Control

Monitoring and control of welding processes 201
Table 10.6 Quality problems identified by ‘Arc Guard’
Problems
Current high or low
Voltage high or low
Shielding-gas failure
Poor arc stability
Wire feed slip
Wire run-out
Stick-out long/stick-out short
Mid-weld power loss
Welding supply failure
some preset parameter are sometimes called programmable error monitors
[225] and these may vary in sophistication from microprocessor-controlled
devices to simple low-cost electronic alarms. [226]
Statistical process control. The ability to transfer or download large volumes
of data to a personal computer allows statistical process control techniques
to be used. [227, 228]. Statistical process control is defined [229] as:
The monitoring and analysis of process conditions using statistical techniques
to accurately determine process performance and preventative or corrective
actions required
It has been shown [230] that the laws of probability may be used to define
predictable limits of variation in quality characteristics, and excursions of
the observed data outside these limits should be taken as an indication of
potential quality problems. In any welding process, there will be a natural
scatter in the observed parameters resulting from inherent process characteristics
and environmental conditions. This natural random scatter is known as ‘common
cause’ variation. Under many circumstances if the process is operating normally
and sufficient data are collected, the values will fall within a standard probability
distribution similar to that shown in Fig. 10.8. If the observed parameters fall
outside the established distribution then abnormal or ‘special cause’ process
disturbances are responsible. By monitoring the process during normal
operation, calculating the sample mean (X m), the range of each sample (R)
and the standard deviation (a), it is possible to set upper and lower control
limits (UCL and LCL, usually = 3s). If any of the parameters subsequently
measured fall outside these control limits, it may be regarded as an indication
of abnormal performance. These techniques may be applied to any welding
process and have been implemented for both the resistance and the arc
monitoring systems described above.
With the arc monitor, control limits may be established in a similar way
by collecting data from normal welding operations and a control chart may
be produced. The effect of abnormal conditions may then be identified by