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The value of good, correlated, historical data can be
immense:
Intermittent
Failure Cause Tracing
The Half-Million Dollar Loose Screw!
As soon as Vsystem was installed and running with
100ms historical data being collected with Vsystem, it happened again at a
paper mill. The web broke. This had cost over $500,000 in the past and
now, at last, the mill engineers had good, correlated data to study from
the motor drives and the PLCs. The data, shown in the picture below, shows
the particular signals that indicate the fault (the analog traces) and the
cause (the digital bars below the analog traces). In tracking down the
problem, the engineers now had many more signals displayed in the window.
Identifying the digitals as being from one PLC block led to the conclusion
that the fault was caused by an intermittent power supply! The freshly
installed monitoring system had paid for itself before its supplier had
even had time to submit the invoice!

Process
Signatures
A plant with a complex process found it difficult to
characterize the process until Vsystem was installed. The Vsystem data
enabled the staff to develop data signatures of key variables indicating
good and bad operations. The screen shot below shows 174 pens or analog
variables used by a plant using Vsystem to monitor the plant operation by
looking for overall signatures and then drilling down to just the signals
of concern by just clicking on the traces that they want removed from the
display.

Predictive
Maintenance
By daily monitoring data collected by Vsystem,
engineers see problems early in their development and can then choose to
either adjust production levels to maintain operation until the next
scheduled maintenance shutdown or schedule an out-of-sequence maintenance
period. This avoids very costly plant trips and allows operators to
confidently operate closer to the edge of the envelope – increasing
normal production as well. When trips to occur, data can determine
if it is safe to restart immediately or if maintenance is required.

Process
Problems and Optimization
By studying relevant Vsystem process data, engineers
can better understand process issues and then implement modifications to
the control of the process or address mechanical issues. The results are
better product, higher and more reliable production, and lower costs.
Modern mathematical techniques can develop computer
models from historical process data. The importance of data
that is fully representing in time all the plant and process measurements
and influences is discussed in this white
paper.
The
Message:
The better the data, the more one can improve the
process, reducing costs and improving quality!
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